Development of Intelligent Fault-Tolerant Control Systems with Machine Learning, Deep Learning, and Transfer Learning Algorithms: A Review

Intelligent Fault-Tolerant Control (IFTC) refers to the applications of machine learning algorithms for fault diagnosis and design of Fault-Tolerant Control (FTC). The overall goal of the FTC is to accommodate defects in the system components while they are in use and maintain stability with little...

Full description

Saved in:
Bibliographic Details
Published inExpert systems with applications Vol. 238; p. 121956
Main Authors Amin, Arslan Ahmed, Sajid Iqbal, Muhammad, Hamza Shahbaz, Muhammad
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 15.03.2024
Subjects
Algorithms
Deep learning
Fault diagnosis
Intelligent fault-tolerant control
Machine learning
Transfer learning
ANN
AE
Intelligent fault-tolerant control
DNN
Transfer learning
JDA
KNN
IFTC
DBM
TDA
Fault diagnosis
Deep learning
TCA
Algorithms
FTC
GAN
Machine learning
RBM
IC Engine
Online AccessGet full text
ISSN0957-4174
1873-6793
DOI10.1016/j.eswa.2023.121956

Cover

Abstract Intelligent Fault-Tolerant Control (IFTC) refers to the applications of machine learning algorithms for fault diagnosis and design of Fault-Tolerant Control (FTC). The overall goal of the FTC is to accommodate defects in the system components while they are in use and maintain stability with little to no performance reduction. These systems are crucial for mission-critical and safety-related applications where the safety of people is at stake and service continuity is crucial. In this review paper, a systematic study has been done for the development of FTC with machine learning, deep learning, and transfer learning algorithms. The challenges and limitations faced with their possible solutions through machine learning theories for the IFTC model are lined up. This paper guides researchers on the different possible types of machine learning algorithms and their advanced forms like deep learning and transfer learning. The differences among these are highlighted by the challenges and limitations of each. The paper is significant such that most of the important literature references from the Scopus database particularly related to important electrical and mechanical industrial problems have been discussed to guide the researchers who want to apply IFTC for specific industrial problems, being the research gap. Finally, future research directions for the development of IFTC are highlighted.
AbstractList Intelligent Fault-Tolerant Control (IFTC) refers to the applications of machine learning algorithms for fault diagnosis and design of Fault-Tolerant Control (FTC). The overall goal of the FTC is to accommodate defects in the system components while they are in use and maintain stability with little to no performance reduction. These systems are crucial for mission-critical and safety-related applications where the safety of people is at stake and service continuity is crucial. In this review paper, a systematic study has been done for the development of FTC with machine learning, deep learning, and transfer learning algorithms. The challenges and limitations faced with their possible solutions through machine learning theories for the IFTC model are lined up. This paper guides researchers on the different possible types of machine learning algorithms and their advanced forms like deep learning and transfer learning. The differences among these are highlighted by the challenges and limitations of each. The paper is significant such that most of the important literature references from the Scopus database particularly related to important electrical and mechanical industrial problems have been discussed to guide the researchers who want to apply IFTC for specific industrial problems, being the research gap. Finally, future research directions for the development of IFTC are highlighted.
ArticleNumber 121956
Author Sajid Iqbal, Muhammad
Amin, Arslan Ahmed
Hamza Shahbaz, Muhammad
Author_xml – sequence: 1
  givenname: Arslan Ahmed
  surname: Amin
  fullname: Amin, Arslan Ahmed
  email: dr.arslanamin@gmail.com
– sequence: 2
  givenname: Muhammad
  surname: Sajid Iqbal
  fullname: Sajid Iqbal, Muhammad
– sequence: 3
  givenname: Muhammad
  surname: Hamza Shahbaz
  fullname: Hamza Shahbaz, Muhammad
BookMark eNp9kM1KAzEUhYMoWH9ewFUewKlJ5idTcVOq1UJF0LoOaeamTUmTksQWX8GndoaKiIuuLufCd-B8Z-jYeQcIXVHSp4RWN6s-xJ3sM8LyPmV0UFZHqEdrnmcVH-THqEcGJc8KyotTdBbjihDKCeE99HUPW7B-swaXsNd44hJYaxZdHMsPm7KZtxBkG0fepeAtfvuMCdYR70xa4meplsYBnoIMzrjFNb4H2PyJ0jV41vJRQ_h946Fd-NDy63iLh_gVtgZ2F-hESxvh8ueeo_fxw2z0lE1fHiej4TRTOSEpU1rnUEtGaEmroqYFKXStSk3nTUHKRhIua86Aw4BVoJuCyrqppKYMqjkryiY_R2zfq4KPMYAWm2DWMnwKSkRnU6xEZ1N0NsXeZgvV_yBlkkymcyKNPYze7VFoR7VDg4jKgFPQmAAqicabQ_g3cE6Urg
CitedBy_id crossref_primary_10_1016_j_jestch_2025_101948
crossref_primary_10_3390_pharmaceutics17030290
crossref_primary_10_1002_adc2_70002
crossref_primary_10_1109_TASE_2024_3395980
crossref_primary_10_1016_j_anucene_2024_110714
crossref_primary_10_1109_TTE_2024_3370298
crossref_primary_10_3390_math13050787
crossref_primary_10_1007_s40860_024_00221_3
crossref_primary_10_1016_j_jpdc_2024_105009
crossref_primary_10_1016_j_measurement_2025_116728
crossref_primary_10_1007_s42405_024_00770_0
crossref_primary_10_1002_cbdv_202401228
crossref_primary_10_1109_JSEN_2025_3528223
crossref_primary_10_3390_w16162272
crossref_primary_10_1007_s00170_025_15361_w
crossref_primary_10_1007_s11227_024_06709_2
crossref_primary_10_1016_j_dche_2025_100227
crossref_primary_10_1088_1361_6501_ad8947
crossref_primary_10_3390_e27010010
crossref_primary_10_1016_j_ress_2024_110134
crossref_primary_10_1109_TASE_2024_3479294
crossref_primary_10_1177_16878132241286781
crossref_primary_10_3390_machines12100729
crossref_primary_10_1007_s11227_025_07109_w
crossref_primary_10_3390_a17100436
crossref_primary_10_3390_app142210587
crossref_primary_10_1109_TASE_2024_3428408
crossref_primary_10_1109_TTE_2024_3363238
crossref_primary_10_1016_j_cnsns_2025_108709
crossref_primary_10_1016_j_flowmeasinst_2024_102730
crossref_primary_10_1177_00202940241231473
crossref_primary_10_1016_j_heliyon_2024_e37964
Cites_doi 10.1016/j.isatra.2017.03.017
10.1016/j.cja.2021.04.022
10.3390/e23111510
10.1016/j.neunet.2014.09.003
10.1016/j.neucom.2018.07.038
10.1098/rsta.2020.0371
10.1109/CCDC.2017.7978168
10.1016/j.measurement.2021.109196
10.1088/1361-6501/acd9df
10.1177/00368504221094723
10.3390/en10010131
10.1371/journal.pone.0279101
10.1016/j.ymssp.2019.106585
10.1177/1475921716652582
10.1109/TIE.2019.2898619
10.1016/j.ymssp.2018.12.051
10.3390/en15197010
10.1177/1077546312463747
10.3390/e20120932
10.1088/1361-6501/aae5b2
10.1016/j.mechmachtheory.2015.03.013
10.1016/j.triboint.2015.12.037
10.1177/1461348417744302
10.1016/j.neucom.2018.05.021
10.1016/j.ymssp.2017.06.022
10.1177/00202940221115233
10.1016/j.rser.2019.04.021
10.1007/s13369-022-07294-3
10.1016/j.aei.2017.02.005
10.1016/j.inffus.2013.10.002
10.1007/s12206-008-0603-6
10.1016/j.isatra.2019.11.003
10.1016/j.knosys.2018.12.019
10.1109/ACCESS.2018.2890566
10.1007/s42417-022-00687-6
10.1016/j.neucom.2013.04.033
10.1016/j.jbi.2018.07.014
10.1016/j.mechmachtheory.2015.11.010
10.1177/16878132231160729
10.1016/j.engappai.2020.103680
10.1093/jcde/qwac028
10.1016/j.measurement.2012.11.011
10.1177/1687814020970311
10.1109/TSG.2014.2386305
10.1038/nature14539
10.1016/j.measurement.2019.04.083
10.3390/s21227587
10.1016/j.isatra.2018.12.025
10.1109/SDPC.2018.8664814
10.1109/JSEN.2017.2726011
10.1016/j.measurement.2012.06.013
10.1109/TIA.2019.2895797
10.1109/TNN.2010.2091281
10.1109/ISFA.2016.7790140
10.1049/iet-smt.2014.0375
10.1049/pel2.12515
10.1109/JESTPE.2021.3115170
10.1177/0020294018823031
10.1016/j.ymssp.2017.01.043
10.1109/MSP.2017.2740460
10.3390/s21103463
10.1016/j.eswa.2020.114060
10.1109/ACCESS.2021.3068164
10.1162/089976600300014782
10.23919/WAC.2018.8430387
10.3126/jist.v26i1.37830
10.1109/TIE.2019.2903774
10.1016/j.sigpro.2016.07.028
10.1109/TIM.2014.2313035
10.1007/s10586-017-0748-0
10.1016/j.ymssp.2019.02.055
10.1155/2019/8716979
10.1049/iet-sen.2017.0053
10.1109/TII.2019.2899118
10.1109/TIE.2018.2877090
10.1016/j.isatra.2021.02.024
10.1016/j.neucom.2015.02.045
10.3390/app8091621
10.1109/TIM.2017.2674738
10.3390/app7050515
10.1561/9781680836394
10.1109/TIE.2018.2866050
10.1016/j.knosys.2018.07.017
10.1007/s12206-017-1205-y
10.1109/eSmarTA56775.2022.9935414
10.1155/2017/5067651
10.1186/s10033-019-0388-9
10.1109/ACCESS.2018.2837621
10.1109/TIE.2018.2844805
10.1109/TIM.2020.3003108
10.1177/0020294019842593
10.1177/0959651819866281
10.1109/ACCESS.2019.2962058
10.1007/s13042-012-0089-5
10.1016/j.ins.2021.08.032
10.3390/s22176448
10.1109/TII.2018.2793246
10.3390/app12157841
10.1109/TIM.2017.2737879
10.3389/fbinf.2022.927312
10.1016/j.ymssp.2018.02.028
10.1016/j.renene.2013.06.025
10.1109/TFUZZ.2019.2893863
10.1016/j.compind.2019.01.008
10.1016/j.jsv.2018.04.036
10.1109/TKDE.2009.191
10.1109/ACCESS.2019.2894796
10.1016/j.cja.2021.09.010
10.1080/17517571003763380
10.1109/TII.2018.2864759
10.1109/ACCESS.2021.3050243
10.1016/j.ymssp.2017.11.024
10.1016/j.jmsy.2018.04.005
10.1007/s40430-015-0455-9
10.1016/j.measurement.2020.108696
10.1016/j.knosys.2022.109773
10.1007/s12206-019-0103-x
10.1109/TIM.2015.2498978
10.1007/s00170-017-1474-8
10.1109/TFUZZ.2021.3053844
10.1016/j.ymssp.2017.03.034
10.1016/j.measurement.2018.05.098
10.1016/j.neucom.2017.07.032
10.1016/j.ymssp.2015.04.039
10.1007/s12206-018-1018-7
10.3390/app8122357
10.1109/LSP.2018.2878356
10.1016/j.eswa.2017.02.030
10.1016/j.ins.2013.09.003
10.1109/TIE.2017.2762639
10.1177/0142331215626247
10.1016/j.engappai.2022.105524
10.1016/j.ymssp.2018.12.032
10.1016/j.ymssp.2016.12.040
10.1016/j.ifacol.2018.09.380
10.3390/s17081729
10.1016/j.patcog.2017.10.013
10.1109/TIE.2020.2994868
10.3390/s18124460
10.1109/TIE.2018.2868023
10.1109/TSMC.2019.2933050
10.1080/17517575.2015.1080860
10.1016/j.ymssp.2012.11.002
10.1016/j.eswa.2018.04.025
10.1109/ACCESS.2021.3126854
10.1061/(ASCE)AS.1943-5525.0000386
10.1109/ACCESS.2017.2693379
10.1145/3065386
10.1109/JSEN.2020.3015868
10.3390/en15155666
10.1109/TSMC.2017.2754287
10.1007/s10916-018-1136-x
10.1016/j.ifacol.2018.09.318
10.1007/s42835-021-00965-5
10.1109/TTE.2021.3071725
10.3390/en9060379
10.1016/j.enconman.2019.111793
10.3390/app8101859
10.1784/insi.2017.59.12.669
10.1145/1273496.1273521
10.1016/j.ymssp.2016.08.005
10.1016/j.measurement.2018.09.013
10.3390/app7010041
10.1177/1687814017743113
10.1109/TGRS.2014.2377785
10.1016/j.apacoust.2016.10.012
10.1109/TIE.2016.2582729
10.1016/j.ymssp.2013.05.017
10.1109/TIE.2016.2627020
10.1016/j.ymssp.2018.05.050
10.1186/s40537-016-0043-6
10.1177/1475921717727700
10.21595/jve.2017.18380
10.1023/A:1008888219539
10.1016/j.knosys.2017.12.027
10.1016/j.ifacol.2022.07.213
10.17531/ein.2017.1.5
10.1016/j.eswa.2022.116794
10.1016/j.neucom.2018.08.046
10.1016/j.amc.2013.12.122
10.1109/ACCESS.2018.2877447
10.1016/j.rser.2022.112128
ContentType Journal Article
Copyright 2023 Elsevier Ltd
Copyright_xml – notice: 2023 Elsevier Ltd
DBID AAYXX
CITATION
DOI 10.1016/j.eswa.2023.121956
DatabaseName CrossRef
DatabaseTitle CrossRef
DatabaseTitleList
DeliveryMethod fulltext_linktorsrc
Discipline Computer Science
EISSN 1873-6793
ExternalDocumentID 10_1016_j_eswa_2023_121956
S0957417423024582
GroupedDBID --K
--M
.DC
.~1
0R~
13V
1B1
1RT
1~.
1~5
4.4
457
4G.
5GY
5VS
7-5
71M
8P~
9JN
9JO
AAAKF
AABNK
AACTN
AAEDT
AAEDW
AAIAV
AAIKJ
AAKOC
AALRI
AAOAW
AAQFI
AARIN
AAXUO
AAYFN
ABBOA
ABFNM
ABMAC
ABMVD
ABUCO
ABYKQ
ACDAQ
ACGFS
ACHRH
ACNTT
ACRLP
ACZNC
ADBBV
ADEZE
ADTZH
AEBSH
AECPX
AEKER
AENEX
AFKWA
AFTJW
AGHFR
AGJBL
AGUBO
AGUMN
AGYEJ
AHHHB
AHJVU
AHZHX
AIALX
AIEXJ
AIKHN
AITUG
AJOXV
ALEQD
ALMA_UNASSIGNED_HOLDINGS
AMFUW
AMRAJ
AOUOD
APLSM
AXJTR
BJAXD
BKOJK
BLXMC
BNSAS
CS3
DU5
EBS
EFJIC
EFLBG
EO8
EO9
EP2
EP3
F5P
FDB
FIRID
FNPLU
FYGXN
G-Q
GBLVA
GBOLZ
HAMUX
IHE
J1W
JJJVA
KOM
LG9
LY1
LY7
M41
MO0
N9A
O-L
O9-
OAUVE
OZT
P-8
P-9
P2P
PC.
PQQKQ
Q38
ROL
RPZ
SDF
SDG
SDP
SDS
SES
SEW
SPC
SPCBC
SSB
SSD
SSL
SST
SSV
SSZ
T5K
TN5
~G-
29G
AAAKG
AAQXK
AATTM
AAXKI
AAYWO
AAYXX
ABJNI
ABKBG
ABUFD
ABWVN
ABXDB
ACLOT
ACNNM
ACRPL
ACVFH
ADCNI
ADJOM
ADMUD
ADNMO
AEIPS
AEUPX
AFJKZ
AFPUW
AGQPQ
AIGII
AIIUN
AKBMS
AKRWK
AKYEP
ANKPU
APXCP
ASPBG
AVWKF
AZFZN
CITATION
EFKBS
EJD
FEDTE
FGOYB
G-2
HLZ
HVGLF
HZ~
R2-
SBC
SET
WUQ
XPP
ZMT
~HD
ID FETCH-LOGICAL-c300t-cff3e8a201516481404f8c5f1bd405da07a872e7e926efd41a8d6af12e6b245d3
IEDL.DBID .~1
ISSN 0957-4174
IngestDate Sat Oct 25 05:47:40 EDT 2025
Thu Apr 24 23:01:08 EDT 2025
Fri Feb 23 02:34:37 EST 2024
IsPeerReviewed true
IsScholarly true
Keywords ANN
AE
Intelligent fault-tolerant control
DNN
Transfer learning
JDA
KNN
IFTC
DBM
TDA
Fault diagnosis
Deep learning
TCA
Algorithms
FTC
GAN
Machine learning
RBM
IC Engine
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c300t-cff3e8a201516481404f8c5f1bd405da07a872e7e926efd41a8d6af12e6b245d3
ParticipantIDs crossref_primary_10_1016_j_eswa_2023_121956
crossref_citationtrail_10_1016_j_eswa_2023_121956
elsevier_sciencedirect_doi_10_1016_j_eswa_2023_121956
PublicationCentury 2000
PublicationDate 2024-03-15
PublicationDateYYYYMMDD 2024-03-15
PublicationDate_xml – month: 03
  year: 2024
  text: 2024-03-15
  day: 15
PublicationDecade 2020
PublicationTitle Expert systems with applications
PublicationYear 2024
Publisher Elsevier Ltd
Publisher_xml – name: Elsevier Ltd
References Shao, Jiang, Zhao, Wang (b0765) 2017; 95
Amin, Mahmood-Ul-Hasan (b0065) 2019; 7
(B. Curless, W. T. Freeman, & L. V. Gool, Eds.). Boston Delft: Now.
He, Wang, Kwong, Wang (b0365) 2014; 259
35.
Li, Yang, Wang, Liu, Liang (b0535) 2018; 428
1–5. Stevenson, WA: IEEE. 10.23919/WAC.2018.8430387.
11.
Xiong, Su, Jiang, Jiang (b0940) 2019; 43
Lu, Liang, Cheng, Meng, Yang, Zhang (b0575) 2017; 64
Cassottana, B., Roomi, M. M., Mashima, D., & Sansavini, G. (n.d.). Resilience analysis of cyber-physical systems: A review of models and methods.
Amin, Mahmood-ul-Hasan (b0070) 2019; 52
Yang, Wang, Zhong (b0990) 2016; 9
Namigtle-Jiménez, Escobar-Jiménez, Gómez-Aguilar, García-Beltrán, Téllez-Anguiano (b0620) 2020; 100
Kim, Choi, Park, Leung, Nasridinov (b0460) 2021; 9
Peebles, P. Z. (2002). Probability. In
Barakat, Lefebvre, Khalil, Druaux, Mustapha (b0120) 2013; 4
Ma, Chu, Han (b0590) 2019; 127
Shi, Zhang (b0780) 2021; 68
Oh, Lee, Lee, Joo, Lee (b0630) 2022; 9
Li, Yan, Tian, Yuan, Peng, Li (b0540) 2013; 46
Lu, Wang, Zhou (b0565) 2017; 32
Wang, Xie, Zhang, Duan (b0845) 2016; 2016
Matasci, Volpi, Kanevski, Bruzzone, Tuia (b0600) 2015; 53
,
Mayer-Schönberger, Cukier (b0605) 2013
Tang, Song, Li, Deng (b0805) 2014; 62
Cai, Weng, Zhang (b0140) 2017; 20
Shao, McAleer, Yan, Baldi (b0770) 2019; 15
Zhai, Yu, Qian, Lee, Theera-Umpon (b1030) 2017; 10
.
Li, Liu, Tang, Lu, Hu (b0505) 2017; 17
Saud, Shakya (b0730) 2021; 26
Yang, Lei, Jia, Xing (b0970) 2019; 122
Han, Tang, Deng (b0350) 2018; 127
Ahmad, Ahmad, Kim (b0010) 2022; 22
Xu, Zhang, Liu, Liu, Liu, Wang, Joe Qin (b0945) 2018; 51
Ma, Xu, Huang, Huang (b0580) 2017; 93
Choudhary, Mian, Fatima (b0200) 2021; 176
Heo, Lee (b0375) 2018; 51
Barakat, El Badaoui, Guillet (b0115) 2013; 37
Riaz, Amin, Tayyeb (b0710) 2022; 105
Dogan, Birant (b0235) 2021; 166
Gerdes, M., Galar, D., & Scholz, D. (2016). Decision trees and the effects of feature extraction parameters for robust sensor network design.
An, Wang, Zhao, Qin, Yan, Chen (b0090) 2022; 71
193–200. Corvalis, Oregon: ACM Press. 10.1145/1273496.1273521.
Naha, Samanta, Routray, Deb (b0615) 2017; 66
Choudhary, Goyal, Letha (b0195) 2021; 21
Long, M., Zhu, H., Wang, J., & Jordan, M. I. (2017). Deep transfer learning with joint adaptation networks.
(5), 646–661. 10.1177/0959651819866281.
Qiao, Lei, Li (b0680) 2019; 122
Bangalore, Tjernberg (b0110) 2015; 6
Zhang, Wang (b1045) 2016; 10
Abdelsalam, Diab, Tennakoon, Griffiths (b0005) 2016
Ince, Kiranyaz, Eren, Askar, Gabbouj (b0385) 2016; 63
Asr, Ettefagh, Hassannejad, Razavi (b0105) 2017; 85
James, Gandhi, Deshmukh (b0400) 2018; 9
Du, Li (b0255) 2023; 16
Dong, Luo, Zhong, Chen, Xu (b0245) 2017; 36
Weiser, Ossmann (b0900) 2022; 55
Yang, Pen, Wang, Chang (b0985) 2016; 65
Qu, He, Deutsch, He (b0685) 2017; 7
Jiang, Shi, Xuan (b0425) 2014; 20
Machine learning, explained. (n.d.). Retrieved December 20, 2022, from MIT Sloan website: https://mitsloan.mit.edu/ideas-made-to-matter/machine-learning-explained.
Dai, W., Yang, Q., Xue, G.-R., & Yu, Y. (2007). Boosting for transfer learning.
Wen, Gao, Li (b0910) 2019; 49
Jiao, Zhao, Lin, Zhao (b0435) 2018; 160
Islam, Kim (b0395) 2019; 106
Wang, He, Li (b0870) 2019; 15
Zhao, Yan, Chen, Mao, Wang, Gao (b1080) 2019; 115
(4th Edition edition). TMH.
Shahbaz, Amin (b0750) 2021; 9
Yu, Zhang, Jiang, Fu, Jin (b1025) 2022; 35
Zhao, Li, Zhang, Zhang (b1090) 2019; 109
Safizadeh, M. S., & Yari, B. (2017). Pump cavitation detection through fusion of support vector machine classifier data associated with vibration and motor current signature. 59(12), 5.
Zhao, Kang, Tang, Pecht (b1075) 2019; 66
Jiang, Zhu, Li, Ren, Zhou, Chang (b0415) 2018; 8
Shahbaz, Amin (b0755) 2023; 15
Yoon, He (b1000) 2015; 9
Dong, L., Li, W., Wang, C.-H., & Lin, K.-P. (2020). Gyro motor fault classification model based on a coupled hidden Markov model with a minimum intra-class distance algorithm.
Zhang, W. J., Yang, G., Lin, Y., Ji, C., & Gupta, M. M. (2018). On Definition of Deep Learning.
Li, Qu, Hong, He (b0500) 2018
Goodfellow, Bengio, Courville (b0295) 2016
(8), 5932–5946. 10.21595/jve.2017.18380.
H. Saltzer, J., & Kaashoek, M. F. (2021, August 1). 2.3: Measures of Reliability and Failure Tolerance. Retrieved August 23, 2023, from Engineering LibreTexts website: https://eng.libretexts.org/Bookshelves/Computer_Science/Programming_and_Computation_Fundamentals/Principles_of_Computer_System_Design_(Saltzer_and_Kaashoek)/02%3A_Fault_Tolerance_-_Reliable_Systems_from_Unreliable_Components/2.03%3A_Measures_of_Reliability_and_Failure_Tolerance.
Mihály, Luca, Cristea (b0610) 2023; Vol. 52
arXiv. Retrieved from http://arxiv.org/abs/2010.01048.
Xie, Du, Shen, Chen, Chen, Zhu (b0925) 2018; 6
(1), 31–42. 10.17531/ein.2017.1.5.
Wang, Wei, Wang, Huang, Peng, Song, Pérez-Jiménez (b0860) 2020; 92
Dong, Xu, Chen (b0250) 2016; 38
Li, Yang, Li, Xu, Huang (b0530) 2017; 91
Urbanowicz, Meeker, La Cava, Olson, Moore (b0820) 2018; 85
Gu, Wang, Kuen, Ma, Shahroudy, Shuai, Chen (b0300) 2018; 77
Wang, Zhang, Xiong, Xiao, Sun, He (b0890) 2017; 17
He, Zhang, Ren, Sun (b0360) 2016
Berredjem, Benidir (b0135) 2018; 108
Saufi, S. R., Ahmad, Z. A. bin, Leong, M. S., & Lim, M. H. (2018). Differential evolution optimization for resilient stacked sparse autoencoder and its applications on bearing fault diagnosis.
Xie, Zhang, Duan, Wang (b0930) 2016; 2016
Zhao, Kang, Tang, Pecht (b1070) 2018; 65
Amin, Mahmood-ul-Hasan (b0080) 2021; 1–16
Xiao, Chen, Chen, Hu, Tang (b0920) 2023; 34
Gharavian, Almas Ganj, Ohadi, Heidari Bafroui (b0285) 2013; 121
Transfer Learning With Neural Networks for Bearing Fault Diagnosis in Changing Working Conditions—IEEE Journals & Magazine. (n.d.). Retrieved February 18, 2021, from https://ieeexplore.ieee.org/abstract/document/7961149.
Peña, Cerrada, Alvarez, Jadán, Lucero, Milton, Sánchez (b0670) 2018; 34
Cao, Tian, Ji, Qiu (b0150) 2021; 7
Diaz, Henriquez, Ferrer, Pirlo, Alonso, Carmona-Duarte, Impedovo (b0225) 2017; 79
Pan, Tsang, Kwok, Yang (b0645) 2011; 22
Wang, Zhou, Qin, Wang (b0880) 2008; 6
Xu, Sun, Liu, Zheng (b0955) 2019; 7
Kumar, Singh, Tripathi (b0470) 2018; 12
Lin, Tan, Ma, Mathew (b0545) 2015; 229
Pudjihartono, Fadason, Kempa-Liehr, O’Sullivan (b0675) 2022; 2
Khan, Yairi (b0450) 2018; 107
Belosludtsev, Borovik, Danilchenko, Sekisov (b0125) 2021; 21
Glowacz, Glowacz (b0290) 2017; 117
Pasqualotto, Zigliotto (b0660) 2022; 10
Sun, Wang, Ding, Xu, Lin (b0795) 2021; 578
(4), 936–945. 10.1177/1475921717727700.
Guo, Lei, Xing, Yan, Li (b0315) 2019; 66
2208–2217. Sydney, NSW, Australia: JMLR.org.
Araste, Sadighi, Jamimoghaddam (b0100) 2023; 11
Krizhevsky, Sutskever, Hinton (b0465) 2017; 60
Tang, Pang, Tian, Zhou (b0810) 2018; 8
Wong, P. K., Zhong, J.-H., Yang, Z.-X., & Vong, C. M. (n.d.). A new framework for intelligent simultaneous-fault diagnosis of rotating machinery using pairwise-coupled sparse Bayesian extreme learning committee machine. 16.
Yang, Liu, Li, Li, Ma (b0980) 2015; 90
Iqbal, Amin (b0390) 2022; 55
Jin, Hou, Chen, Lu (b0440) 2022; 35
Savchynskyy, B. (2019).
Chen, C., Li, Z., Yang, J., & Liang, B. (2017). A cross domain feature extraction method based on transfer component analysis for rolling bearing fault diagnosis.
Zhang, Yang, Kong, Chen, Fu, Peng (b1035) 2021; 51
Duan, Wu, Guo, Shao, Malekian, Li (b0260) 2018; 96
Wang (b0865) 2020; 69
Schmidhuber (b0745) 2015; 61
Shao, Jiang, Wang, Wang (b0760) 2017; 69
Amarnath, Sugumaran, Kumar (b0055) 2013; 46
Li, Xu, Zhao, Huang (b0525) 2016; 98
Khazaee, Banakar, Ghobadian, Mirsalim, Minaei, Jafari, Sharghi (b0455) 2016; 15
Cao, Zhang, Tang (b0145) 2018; 6
Safizadeh, Latifi (b0720) 2014; 18
Dai, Tang, Huang, Wang (b0205) 2019; 32
Han, Liu, Yang, Jiang (b0345) 2019; 165
Hongyan dui (b0380) 2015; 12
Zhang, Lin (b1040) 2010; 4
Zheng, Wang, Yang, Li, Xu (b1095) 2020; 67
Long, Wang, Cao, Sun, Yu (b0550) 2016; 99
Jia, Xu, Wang (b0410) 2018; 18
Li, Chuan. (n.d.). Gearbox fault diagnosis based on deep random forest fusion of acoustic and vibratory signals.
Singh, Shaik (b0790) 2019; 131
1–6. Ibb, Yemen: IEEE. 10.1109/eSmarTA56775.2022.9935414.
Alsuwian, Amin, Iqbal, Qadir, Almasabi, Jalalah (b0035) 2022; 17
Wang, Fan (b0885) 2015; 28
Amin, Mahmood-ul-Hasan (b0085) 2022; 17
Zhang, Li, Ding (b1060) 2019; 95
Ali, Shabbir, Liang, Zhang, Hu (b0025) 2019; 55
Xie, Zhang (b0935) 2018; 2018
Amin, Mahmood-ul-Hasan (b0075) 2019; 52
Nezamivand Chegini, Haghdoust Manjili, Ahmadi, Amirmostofian, Bagheri (b0625) 2021; 170
Yu, Ding, He (b1015) 2018; 32
Bernier, Ortega, Ros, Rojas, Prieto (b0130) 2000; 12
Hasan, Kim (b0355) 2018; 8
Pang, Tang, Zhou, Tian (b0650) 2018; 20
Chikkam, Singh (b0190) 2023; 48
Deep Learning Enabled Fault Diagnosis Using Time-Frequency Image Analysis of Rolling Element Bearings. (n.d.). Retrieved February 19, 2021, from https://www.hindawi.com/journals/sv/2017/5067651/.
Li, G., Gu, Y., & Ding, J. (2020, October 2).
Yu, Huang, Zhao (b1020) 2016; 230
Cervantes-Bobadilla, García-Morales, Saavedra-Benítez, Hernández-Pérez, Adam-Medina, Guerrero-Ramírez, Escobar-Jímenez (b0160) 2023; 117
(n/a). 10.1111/risa.14089.
Wang, Xiang, Zhong, Zhou (b0855) 2018; 144
Hallajian, Motameni, Akbari (b0330) 2022; 200
Zhang, Li, Gao, Wang, Wen (b1065) 2018; 48
Yu, Wang, Li (b1005) 2018; 25
Yu, Bai, Wang, Shi (b1010) 2018; 32
Han, Zhao, Shi (b0335) 2017; 9
Rai, Upadhyay (b0690) 2016; 96
Ali, Y. H., H. Ahmed, F. Y., Abdelrhman, A. M., Ali, S. M., Borhana, A. A., & Ishak Raja Hamzah, R. (2022). Novel Spiking Neural Network Model for Gear Fault Diagnosis.
Shen, Chen, Yan, Gao (b0270) 2015
Ma, Sun, Chen (b0585) 2018; 14
Wang, Chen, Guan (b0850) 2021; 118
Van, Kang (b0825) 2016; 230
LeCun, Bengio, Hinton (b0475) 2015; 521
Vanraj, Dhami, S., & Pabla, B. (2018). Hybrid data fusion approach for fault diagnosis of fixed-axis gearbox.
Kafeel, Aziz, Awais, Khan, Afaq, Idris, Mostafa (b0445) 2021; 21
Wang, Xiang, Markert, Liang (b0875) 2016; 66–67
Guo, Shen, Chen (b0320) 2017; 7
Xu, Lei, Li (b0950) 2020; 67
Zhao, Jia (b1085) 2018; 315
Research on Degradation State Recognition of Planetary Gear Based on Multiscale Information Dimension of SSD and CNN. (n.d.). Retrieved February 19, 2021, from https://www.hindawi.com/journals/complexity/2019/8716979/.
Wang, Qian, Yan, Yuan, Zhang
10.1016/j.eswa.2023.121956_b0560
Oh (10.1016/j.eswa.2023.121956_b0630) 2022; 9
Pang (10.1016/j.eswa.2023.121956_b0650) 2018; 20
Urbanowicz (10.1016/j.eswa.2023.121956_b0820) 2018; 85
Wang (10.1016/j.eswa.2023.121956_b0850) 2021; 118
Gelgele (10.1016/j.eswa.2023.121956_b0275) 1998; 9
10.1016/j.eswa.2023.121956_b0325
Amin (10.1016/j.eswa.2023.121956_b0080) 2021; 1–16
Li (10.1016/j.eswa.2023.121956_b0520) 2018; 310
Belosludtsev (10.1016/j.eswa.2023.121956_b0125) 2021; 21
He (10.1016/j.eswa.2023.121956_b0360) 2016
Xiong (10.1016/j.eswa.2023.121956_b0940) 2019; 43
Ahmad (10.1016/j.eswa.2023.121956_b0015) 2022; 160
Yang (10.1016/j.eswa.2023.121956_b0990) 2016; 9
Jiang (10.1016/j.eswa.2023.121956_b0415) 2018; 8
10.1016/j.eswa.2023.121956_b0210
He (10.1016/j.eswa.2023.121956_b0365) 2014; 259
10.1016/j.eswa.2023.121956_b0695
Yu (10.1016/j.eswa.2023.121956_b1020) 2016; 230
Barakat (10.1016/j.eswa.2023.121956_b0120) 2013; 4
An (10.1016/j.eswa.2023.121956_b0090) 2022; 71
10.1016/j.eswa.2023.121956_b0215
Zhang (10.1016/j.eswa.2023.121956_b1055) 2018; 100
Han (10.1016/j.eswa.2023.121956_b0350) 2018; 127
Ince (10.1016/j.eswa.2023.121956_b0385) 2016; 63
Yu (10.1016/j.eswa.2023.121956_b1005) 2018; 25
Bangalore (10.1016/j.eswa.2023.121956_b0110) 2015; 6
Gharavian (10.1016/j.eswa.2023.121956_b0285) 2013; 121
Tang (10.1016/j.eswa.2023.121956_b0805) 2014; 62
Han (10.1016/j.eswa.2023.121956_b0340) 2020; 1–11
Matasci (10.1016/j.eswa.2023.121956_b0600) 2015; 53
James (10.1016/j.eswa.2023.121956_b0400) 2018; 9
Jiao (10.1016/j.eswa.2023.121956_b0435) 2018; 160
Li (10.1016/j.eswa.2023.121956_b0480) 2022; 255
Riaz (10.1016/j.eswa.2023.121956_b0710) 2022; 105
10.1016/j.eswa.2023.121956_b0220
Wang (10.1016/j.eswa.2023.121956_b0875) 2016; 66–67
Choudhary (10.1016/j.eswa.2023.121956_b0195) 2021; 21
Krizhevsky (10.1016/j.eswa.2023.121956_b0465) 2017; 60
Yadav (10.1016/j.eswa.2023.121956_b0960) 2021
Amin (10.1016/j.eswa.2023.121956_b0070) 2019; 52
Wang (10.1016/j.eswa.2023.121956_b0890) 2017; 17
Iqbal (10.1016/j.eswa.2023.121956_b0390) 2022; 55
Jiang (10.1016/j.eswa.2023.121956_b0430) 2013; 41
Dong (10.1016/j.eswa.2023.121956_b0245) 2017; 36
Dogan (10.1016/j.eswa.2023.121956_b0235) 2021; 166
Li (10.1016/j.eswa.2023.121956_b0535) 2018; 428
Li (10.1016/j.eswa.2023.121956_b0495) 2005
Goodfellow (10.1016/j.eswa.2023.121956_b0295) 2016
Wang (10.1016/j.eswa.2023.121956_b0880) 2008; 6
Hallajian (10.1016/j.eswa.2023.121956_b0330) 2022; 200
Zhang (10.1016/j.eswa.2023.121956_b1045) 2016; 10
Han (10.1016/j.eswa.2023.121956_b0345) 2019; 165
Li (10.1016/j.eswa.2023.121956_b0500) 2018
10.1016/j.eswa.2023.121956_b0595
Alsuwian (10.1016/j.eswa.2023.121956_b0045) 2022; 15
Shifat (10.1016/j.eswa.2023.121956_b0785) 2021; 9
10.1016/j.eswa.2023.121956_b0915
Yang (10.1016/j.eswa.2023.121956_b0975) 2008; 22
Nezamivand Chegini (10.1016/j.eswa.2023.121956_b0625) 2021; 170
Van (10.1016/j.eswa.2023.121956_b0825) 2016; 230
10.1016/j.eswa.2023.121956_b1050
Xie (10.1016/j.eswa.2023.121956_b0935) 2018; 2018
Qiao (10.1016/j.eswa.2023.121956_b0680) 2019; 122
Safizadeh (10.1016/j.eswa.2023.121956_b0720) 2014; 18
Rai (10.1016/j.eswa.2023.121956_b0690) 2016; 96
Lu (10.1016/j.eswa.2023.121956_b0570) 2017; 130
Qu (10.1016/j.eswa.2023.121956_b0685) 2017; 7
Dai (10.1016/j.eswa.2023.121956_b0205) 2019; 32
Wang (10.1016/j.eswa.2023.121956_b0860) 2020; 92
Ahmad (10.1016/j.eswa.2023.121956_b0010) 2022; 22
Li (10.1016/j.eswa.2023.121956_b0515) 2019; 66
Barakat (10.1016/j.eswa.2023.121956_b0115) 2013; 37
Shahbaz (10.1016/j.eswa.2023.121956_b0755) 2023; 15
10.1016/j.eswa.2023.121956_b0895
10.1016/j.eswa.2023.121956_b0775
Schmidhuber (10.1016/j.eswa.2023.121956_b0745) 2015; 61
Yu (10.1016/j.eswa.2023.121956_b1010) 2018; 32
Araste (10.1016/j.eswa.2023.121956_b0100) 2023; 11
LeCun (10.1016/j.eswa.2023.121956_b0475) 2015; 521
Ma (10.1016/j.eswa.2023.121956_b0580) 2017; 93
Pan (10.1016/j.eswa.2023.121956_b0640) 2010; 22
Zheng (10.1016/j.eswa.2023.121956_b1095) 2020; 67
Diaz (10.1016/j.eswa.2023.121956_b0225) 2017; 79
Zhao (10.1016/j.eswa.2023.121956_b1085) 2018; 315
Chen (10.1016/j.eswa.2023.121956_b0170) 2021; 379
Wang (10.1016/j.eswa.2023.121956_b0865) 2020; 69
Weiser (10.1016/j.eswa.2023.121956_b0900) 2022; 55
Yang (10.1016/j.eswa.2023.121956_b0980) 2015; 90
Yang (10.1016/j.eswa.2023.121956_b0970) 2019; 122
Mihály (10.1016/j.eswa.2023.121956_b0610) 2023; Vol. 52
Yu (10.1016/j.eswa.2023.121956_b1025) 2022; 35
10.1016/j.eswa.2023.121956_b0665
Choudhary (10.1016/j.eswa.2023.121956_b0200) 2021; 176
Zhang (10.1016/j.eswa.2023.121956_b1060) 2019; 95
Bernier (10.1016/j.eswa.2023.121956_b0130) 2000; 12
Zhao (10.1016/j.eswa.2023.121956_b1075) 2019; 66
Zhao (10.1016/j.eswa.2023.121956_b1090) 2019; 109
Wang (10.1016/j.eswa.2023.121956_b0840) 2020; 8
Park (10.1016/j.eswa.2023.121956_b0655) 2018; 108
Oroojlooy (10.1016/j.eswa.2023.121956_b0635) 2022; 1–46
Lin (10.1016/j.eswa.2023.121956_b0545) 2015; 229
Guo (10.1016/j.eswa.2023.121956_b0315) 2019; 66
Yu (10.1016/j.eswa.2023.121956_b1015) 2018; 32
Zhang (10.1016/j.eswa.2023.121956_b1040) 2010; 4
Jin (10.1016/j.eswa.2023.121956_b0440) 2022; 35
Rezvani (10.1016/j.eswa.2023.121956_b0705) 2019; 27
Wang (10.1016/j.eswa.2023.121956_b0845) 2016; 2016
Shao (10.1016/j.eswa.2023.121956_b0765) 2017; 95
Saud (10.1016/j.eswa.2023.121956_b0730) 2021; 26
Amin (10.1016/j.eswa.2023.121956_b0060) 2019; 143
Pan (10.1016/j.eswa.2023.121956_b0645) 2011; 22
Yoon (10.1016/j.eswa.2023.121956_b1000) 2015; 9
Xu (10.1016/j.eswa.2023.121956_b0945) 2018; 51
Zhang (10.1016/j.eswa.2023.121956_b1065) 2018; 48
Mayer-Schönberger (10.1016/j.eswa.2023.121956_b0605) 2013
10.1016/j.eswa.2023.121956_b0280
Xu (10.1016/j.eswa.2023.121956_b0950) 2020; 67
Lu (10.1016/j.eswa.2023.121956_b0565) 2017; 32
Jia (10.1016/j.eswa.2023.121956_b0410) 2018; 18
10.1016/j.eswa.2023.121956_b0165
Shahbaz (10.1016/j.eswa.2023.121956_b0750) 2021; 9
Amin (10.1016/j.eswa.2023.121956_b0085) 2022; 17
Ma (10.1016/j.eswa.2023.121956_b0590) 2019; 127
Ding (10.1016/j.eswa.2023.121956_b0230) 2017; 66
Jiang (10.1016/j.eswa.2023.121956_b0425) 2014; 20
Amin (10.1016/j.eswa.2023.121956_b0075) 2019; 52
10.1016/j.eswa.2023.121956_b0965
10.1016/j.eswa.2023.121956_b0725
Lu (10.1016/j.eswa.2023.121956_b0575) 2017; 64
Zhao (10.1016/j.eswa.2023.121956_b1070) 2018; 65
Han (10.1016/j.eswa.2023.121956_b0335) 2017; 9
Namigtle-Jiménez (10.1016/j.eswa.2023.121956_b0620) 2020; 100
Kafeel (10.1016/j.eswa.2023.121956_b0445) 2021; 21
Cai (10.1016/j.eswa.2023.121956_b0140) 2017; 20
Khan (10.1016/j.eswa.2023.121956_b0450) 2018; 107
Pasqualotto (10.1016/j.eswa.2023.121956_b0660) 2022; 10
Zhai (10.1016/j.eswa.2023.121956_b1030) 2017; 10
10.1016/j.eswa.2023.121956_b0175
Gu (10.1016/j.eswa.2023.121956_b0300) 2018; 77
Alsuwian (10.1016/j.eswa.2023.121956_b0040) 2022; 12
Guo (10.1016/j.eswa.2023.121956_b0310) 2018; 319
10.1016/j.eswa.2023.121956_b0735
Guo (10.1016/j.eswa.2023.121956_b0320) 2017; 7
Cervantes-Bobadilla (10.1016/j.eswa.2023.121956_b0160) 2023; 117
Gunerkar (10.1016/j.eswa.2023.121956_b0305) 2019; 33
Long (10.1016/j.eswa.2023.121956_b0555) 2013
Li (10.1016/j.eswa.2023.121956_b0510) 2014; 63
Du (10.1016/j.eswa.2023.121956_b0255) 2023; 16
Khazaee (10.1016/j.eswa.2023.121956_b0455) 2016; 15
Jia (10.1016/j.eswa.2023.121956_b0405) 2018; 272
10.1016/j.eswa.2023.121956_b0740
Xu (10.1016/j.eswa.2023.121956_b0955) 2019; 7
Ahmed (10.1016/j.eswa.2023.121956_b0020) 2020; 12
An (10.1016/j.eswa.2023.121956_b0095) 2017; 39
Dong (10.1016/j.eswa.2023.121956_b0250) 2016; 38
Wang (10.1016/j.eswa.2023.121956_b0870) 2019; 15
Pudjihartono (10.1016/j.eswa.2023.121956_b0675) 2022; 2
Zhang (10.1016/j.eswa.2023.121956_b1035) 2021; 51
Hendrickx (10.1016/j.eswa.2023.121956_b0370) 2020; 139
Hasan (10.1016/j.eswa.2023.121956_b0355) 2018; 8
Alsuwian (10.1016/j.eswa.2023.121956_b0050) 2022; 15
Kumar (10.1016/j.eswa.2023.121956_b0470) 2018; 12
Yao (10.1016/j.eswa.2023.121956_b0995) 2017; 5
Abdelsalam (10.1016/j.eswa.2023.121956_b0005) 2016
Chikkam (10.1016/j.eswa.2023.121956_b0190) 2023; 48
Shen (10.1016/j.eswa.2023.121956_b0270) 2015
Reyes (10.1016/j.eswa.2023.121956_b0700) 2015; 161
Li (10.1016/j.eswa.2023.121956_b0525) 2016; 98
Sun (10.1016/j.eswa.2023.121956_b0800) 2022; 30
Glowacz (10.1016/j.eswa.2023.121956_b0290) 2017; 117
Hongyan dui (10.1016/j.eswa.2023.121956_b0380) 2015; 12
Shao (10.1016/j.eswa.2023.121956_b0760) 2017; 69
Alsuwian (10.1016/j.eswa.2023.121956_b0035) 2022; 17
Xie (10.1016/j.eswa.2023.121956_b0925) 2018; 6
10.1016/j.eswa.2023.121956_b0240
10.1016/j.eswa.2023.121956_b0485
Asr (10.1016/j.eswa.2023.121956_b0105) 2017; 85
Peña (10.1016/j.eswa.2023.121956_b0670) 2018; 34
Berredjem (10.1016/j.eswa.2023.121956_b0135) 2018; 108
Amin (10.1016/j.eswa.2023.121956_b0065) 2019; 7
Jiang (10.1016/j.eswa.2023.121956_b0420) 2019; 66
Wang (10.1016/j.eswa.2023.121956_b0885) 2015; 28
Weiss (10.1016/j.eswa.2023.121956_b0905) 2016; 3
Singh (10.1016/j.eswa.2023.121956_b0790) 2019; 131
10.1016/j.eswa.2023.121956_b0490
Chen (10.1016/j.eswa.2023.121956_b0185) 2019; 198
Wen (10.1016/j.eswa.2023.121956_b0910) 2019; 49
Cao (10.1016/j.eswa.2023.121956_b0145) 2018; 6
Naha (10.1016/j.eswa.2023.121956_b0615) 2017; 66
Chen (10.1016/j.eswa.2023.121956_b0180) 2014; 230
Duan (10.1016/j.eswa.2023.121956_b0260) 2018; 96
10.1016/j.eswa.2023.121956_b0815
Zhao (10.1016/j.eswa.2023.121956_b1080) 2019; 115
Yang (10.1016/j.eswa.2023.121956_b0985) 2016; 65
Long (10.1016/j.eswa.2023.121956_b0550) 2016; 99
Tang (10.1016/j.eswa.2023.121956_b0810) 2018; 8
Xie (10.1016/j.eswa.2023.121956_b0930) 2016; 2016
Sun (10.1016/j.eswa.2023.121956_b0795) 2021; 578
Venkateswara (10.1016/j.eswa.2023.121956_b0835) 2017; 34
Wang (10.1016/j.eswa.2023.121956_b0855) 2018; 144
Li (10.1016/j.eswa.2023.121956_b0540) 2013; 46
Amarnath (10.1016/j.eswa.2023.121956_b0055) 2013; 46
Dubrova (10.1016/j.eswa.2023.121956_b0265) 2013
Ma (10.1016/j.eswa.2023.121956_b0585) 2018; 14
Cao (10.1016/j.eswa.2023.121956_b0150) 2021; 7
10.1016/j.eswa.2023.121956_b0030
Kim (10.1016/j.eswa.2023.121956_b0460) 2021; 9
Li (10.1016/j.eswa.2023.121956_b0530) 2017; 91
Shao (10.1016/j.eswa.2023.121956_b0770) 2019; 15
10.1016/j.eswa.2023.121956_b0155
Heo (10.1016/j.eswa.2023.121956_b0375) 2018; 51
10.1016/j.eswa.2023.121956_b0830
Shi (10.1016/j.eswa.2023.
References_xml – volume: 17
  start-page: e0279101
  year: 2022
  ident: b0035
  article-title: Design of active Fault-Tolerant control system for Air-Fuel ratio control of internal combustion engine using nonlinear regression-based observer model
  publication-title: PLoS One1
– volume: 65
  start-page: 11
  year: 2016
  ident: b0985
  article-title: Feature knowledge based fault detection of induction motors through the analysis of stator current data
  publication-title: IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
– volume: 63
  start-page: 7067
  year: 2016
  end-page: 7075
  ident: b0385
  article-title: Real-Time motor fault detection by 1-D convolutional neural networks
  publication-title: IEEE Transactions on Industrial Electronics
– volume: 67
  start-page: 1293
  year: 2020
  end-page: 1304
  ident: b1095
  article-title: Intelligent fault identification based on multisource domain generalization towards actual diagnosis scenario
  publication-title: IEEE Transactions on Industrial Electronics
– reference: , 1–6. Ibb, Yemen: IEEE. 10.1109/eSmarTA56775.2022.9935414.
– volume: 36
  start-page: 354
  year: 2017
  end-page: 365
  ident: b0245
  article-title: Fault diagnosis of bearing based on the Kernel principal component analysis and optimized
  publication-title: Journal of Low Frequency Noise, Vibration and Active Control
– volume: 32
  start-page: 5201
  year: 2018
  end-page: 5211
  ident: b1015
  article-title: Rolling bearing fault diagnosis based on mean multigranulation decision-theoretic rough set and non-naive bayesian classifier
  publication-title: Journal of Mechanical Science and Technology
– volume: 379
  start-page: 20200371
  year: 2021
  ident: b0170
  article-title: Stochastic model predictive control framework for resilient cyber-physical systems: Review and perspectives
  publication-title: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
– reference: Ali, Y. H., H. Ahmed, F. Y., Abdelrhman, A. M., Ali, S. M., Borhana, A. A., & Ishak Raja Hamzah, R. (2022). Novel Spiking Neural Network Model for Gear Fault Diagnosis.
– volume: 16
  start-page: 1969
  year: 2023
  end-page: 1983
  ident: b0255
  article-title: Passive fault-tolerant control for discrete parameter system
  publication-title: IET Power Electronics
– volume: 200
  year: 2022
  ident: b0330
  article-title: Ensemble feature selection using distance-based supervised and unsupervised methods in binary classification
  publication-title: Expert Systems with Applications
– reference: Cassottana, B., Roomi, M. M., Mashima, D., & Sansavini, G. (n.d.). Resilience analysis of cyber-physical systems: A review of models and methods.
– reference: Transfer Learning With Neural Networks for Bearing Fault Diagnosis in Changing Working Conditions—IEEE Journals & Magazine. (n.d.). Retrieved February 18, 2021, from https://ieeexplore.ieee.org/abstract/document/7961149.
– volume: 3
  start-page: 9
  year: 2016
  ident: b0905
  article-title: A survey of transfer learning
  publication-title: Journal of Big Data
– volume: 121
  start-page: 150
  year: 2013
  end-page: 159
  ident: b0285
  article-title: Comparison of FDA-based and PCA-based features in fault diagnosis of automobile gearboxes
  publication-title: Neurocomputing
– volume: 315
  start-page: 447
  year: 2018
  end-page: 464
  ident: b1085
  article-title: Fault diagnosis of rolling bearing based on feature reduction with global-local margin fisher analysis
  publication-title: Neurocomputing
– volume: 6
  start-page: 339
  year: 2008
  end-page: 350
  ident: b0880
  article-title: Active Fault-Tolerant control for a class of nonlinear systems with sensor faults
  publication-title: International Journal of control, Automation, and systems
– reference: Wong, P. K., Zhong, J.-H., Yang, Z.-X., & Vong, C. M. (n.d.). A new framework for intelligent simultaneous-fault diagnosis of rotating machinery using pairwise-coupled sparse Bayesian extreme learning committee machine. 16.
– reference: . arXiv. Retrieved from http://arxiv.org/abs/2010.01048.
– volume: 160
  start-page: 237
  year: 2018
  end-page: 250
  ident: b0435
  article-title: A multivariate encoder information based convolutional neural network for intelligent fault diagnosis of planetary gearboxes
  publication-title: Knowledge-Based Systems
– volume: 230
  start-page: 542
  year: 2014
  end-page: 554
  ident: b0180
  article-title: Fault diagnosis based on comprehensive geometric characteristic and probability neural network
  publication-title: Applied Mathematics and Computation
– volume: 9
  start-page: 539
  year: 1998
  end-page: 545
  ident: b0275
  article-title: An expert system for engine fault diagnosis: Development and application
  publication-title: Journal of Intelligent Manufacturing
– volume: 37
  start-page: 276
  year: 2013
  end-page: 292
  ident: b0115
  article-title: Hard competitive growing neural network for the diagnosis of small bearing faults
  publication-title: Mechanical Systems and Signal Processing
– volume: 34
  year: 2023
  ident: b0920
  article-title: Intelligent fault diagnosis of gear crack based on side frequency feature under different working conditions
  publication-title: Measurement Science and Technology
– reference: Peebles, P. Z. (2002). Probability. In
– volume: 30
  start-page: 1197
  year: 2022
  end-page: 1211
  ident: b0800
  article-title: Feature selection with missing labels using multilabel fuzzy neighborhood rough sets and maximum relevance minimum redundancy
  publication-title: IEEE Transactions on fuzzy Systems
– volume: 61
  start-page: 85
  year: 2015
  end-page: 117
  ident: b0745
  article-title: Deep learning in neural networks: an overview
  publication-title: Neural Networks
– reference: (1st ed.). (2021). Wiley. 10.1002/9781119882350.
– volume: 77
  start-page: 354
  year: 2018
  end-page: 377
  ident: b0300
  article-title: Recent advances in convolutional neural networks
  publication-title: Pattern Recognition
– volume: 9
  year: 2017
  ident: b0335
  article-title: A new fault diagnosis method based on deep belief network and support vector machine with Teager-Kaiser energy operator for bearings
  publication-title: Advances in Mechanical Engineering
– volume: 17
  start-page: 5581
  year: 2017
  end-page: 5588
  ident: b0890
  article-title: Fault diagnosis of a rolling bearing using wavelet packet denoising and random forests
  publication-title: IEEE Sensors Journal
– volume: 9
  start-page: 46022
  year: 2021
  end-page: 46032
  ident: b0750
  article-title: Design of active fault tolerant control system for air fuel ratio control of internal combustion engines using artificial neural networks
  publication-title: IEEE Access
– volume: 115
  start-page: 213
  year: 2019
  end-page: 237
  ident: b1080
  article-title: Deep learning and its applications to machine health monitoring
  publication-title: Mechanical Systems and Signal Processing
– volume: 7
  start-page: 515
  year: 2017
  ident: b0685
  article-title: Detection of pitting in gears using a deep sparse autoencoder
  publication-title: Applied Sciences
– reference: , 193–200. Corvalis, Oregon: ACM Press. 10.1145/1273496.1273521.
– volume: 428
  start-page: 72
  year: 2018
  end-page: 86
  ident: b0535
  article-title: Early fault diagnosis of rolling bearings based on hierarchical symbol dynamic entropy and binary tree support vector machine
  publication-title: Journal of Sound and Vibration
– volume: 12
  start-page: 297
  year: 2015
  end-page: 300
  ident: b0380
  article-title: Reliability optimization of automatic control systems based on importance measures: A framework
  publication-title: International Journal of Performability Engineering
– volume: 66
  start-page: 3249
  year: 2017
  end-page: 3259
  ident: b0615
  article-title: Low complexity motor current signature analysis using Sub-Nyquist strategy with reduced data length
  publication-title: IEEE Transactions on Instrumentation and Measurement
– volume: 46
  start-page: 1250
  year: 2013
  end-page: 1256
  ident: b0055
  article-title: Exploiting sound signals for fault diagnosis of bearings using decision tree
  publication-title: Measurement
– volume: 8
  start-page: 2357
  year: 2018
  ident: b0355
  article-title: Bearing fault diagnosis under variable rotational speeds using stockwell Transform-Based vibration imaging and transfer learning
  publication-title: Applied Sciences
– volume: 108
  start-page: 262
  year: 2018
  end-page: 275
  ident: b0655
  article-title: Gear fault diagnosis using transmission error and ensemble empirical mode decomposition
  publication-title: Mechanical Systems and Signal Processing
– volume: 15
  start-page: 5666
  year: 2022
  ident: b0050
  article-title: Design of a hybrid Fault-Tolerant control system for Air-Fuel ratio control of internal combustion engines using genetic algorithm and Higher-Order sliding mode control
  publication-title: Energies
– volume: 55
  start-page: 703
  year: 2022
  end-page: 716
  ident: b0390
  article-title: Genetic algorithm based active fault-tolerant control system for air fuel ratio control of internal combustion engines
  publication-title: Measurement and Control
– volume: 160
  year: 2022
  ident: b0015
  article-title: Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the context of smart grid paradigm
  publication-title: Renewable and Sustainable Energy Reviews
– volume: 2016
  start-page: 1
  year: 2016
  end-page: 6
  ident: b0930
  article-title: on cross-domain feature fusion in gearbox fault diagnosis under various operating conditions based on transfer component analysis
  publication-title: IEEE International Conference on Prognostics and Health Management (ICPHM)
– volume: 7
  start-page: 2530
  year: 2021
  end-page: 2540
  ident: b0150
  article-title: Fault-Tolerant controller design for path following of the autonomous vehicle under the faults in braking actuators
  publication-title: IEEE Transactions on Transportation Electrification
– volume: 52
  start-page: 1179
  year: 2019
  end-page: 1194
  ident: b0075
  article-title: Robust active fault-tolerant control for internal combustion gas engine for air–fuel ratio control with statistical regression-based observer model
  publication-title: Measurement and Control
– volume: 9
  start-page: 9429
  year: 2021
  end-page: 9441
  ident: b0785
  article-title: ANN assisted multi sensor information fusion for BLDC motor fault diagnosis
  publication-title: IEEE Access
– reference: Dai, W., Yang, Q., Xue, G.-R., & Yu, Y. (2007). Boosting for transfer learning.
– volume: 62
  start-page: 1
  year: 2014
  end-page: 9
  ident: b0805
  article-title: Fault diagnosis for a wind turbine transmission system based on manifold learning and shannon wavelet support vector machine
  publication-title: Renewable Energy
– volume: 98
  start-page: 114
  year: 2016
  end-page: 132
  ident: b0525
  article-title: Hierarchical fuzzy entropy and improved support vector machine based binary tree approach for rolling bearing fault diagnosis
  publication-title: Mechanism and Machine Theory
– volume: 109
  start-page: 85
  year: 2019
  end-page: 101
  ident: b1090
  article-title: Artificial intelligence-based fault detection and diagnosis methods for building energy systems: Advantages, challenges and the future
  publication-title: Renewable and Sustainable Energy Reviews
– volume: 10
  start-page: 2042
  year: 2022
  end-page: 2051
  ident: b0660
  article-title: increasing feasibility of neural Network-Based early fault detection in induction motor drives
  publication-title: IEEE Journal of Emerging and Selected Topics in Power Electronics
– volume: 64
  start-page: 2296
  year: 2017
  end-page: 2305
  ident: b0575
  article-title: Deep model based domain adaptation for fault diagnosis
  publication-title: IEEE Transactions on Industrial Electronics
– volume: 176
  year: 2021
  ident: b0200
  article-title: Convolutional neural network based bearing fault diagnosis of rotating machine using thermal images
  publication-title: Measurement
– volume: 130
  start-page: 377
  year: 2017
  end-page: 388
  ident: b0570
  article-title: Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification
  publication-title: Signal Processing
– volume: 117
  start-page: 20
  year: 2017
  end-page: 27
  ident: b0290
  article-title: Diagnosis of stator faults of the single-phase induction motor using acoustic signals
  publication-title: Applied Acoustics
– volume: 22
  start-page: 199
  year: 2011
  end-page: 210
  ident: b0645
  article-title: Domain adaptation via transfer component analysis
  publication-title: IEEE Transactions on Neural Networks
– volume: 32
  start-page: 139
  year: 2017
  end-page: 151
  ident: b0565
  article-title: Intelligent fault diagnosis of rolling bearing using hierarchical convolutional network based health state classification
  publication-title: Advanced Engineering Informatics
– volume: 96
  start-page: 289
  year: 2016
  end-page: 306
  ident: b0690
  article-title: A review on signal processing techniques utilized in the fault diagnosis of rolling element bearings
  publication-title: Tribology international
– volume: 20
  start-page: 932
  year: 2018
  ident: b0650
  article-title: Rotor fault diagnosis based on characteristic frequency band energy entropy and support vector machine
  publication-title: Entropy
– volume: 100
  start-page: 439
  year: 2018
  end-page: 453
  ident: b1055
  article-title: A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load
  publication-title: Mechanical Systems and Signal Processing
– volume: 117
  year: 2023
  ident: b0160
  article-title: Multiple fault detection and isolation using artificial neural networks in sensors of an internal combustion engine
  publication-title: Engineering Applications of Artificial Intelligence
– volume: 14
  start-page: 1137
  year: 2018
  end-page: 1145
  ident: b0585
  article-title: Deep coupling autoencoder for fault diagnosis with multimodal sensory data
  publication-title: IEEE Transactions on Industrial Informatics
– volume: 21
  start-page: 7587
  year: 2021
  ident: b0445
  article-title: An expert system for rotating machine fault detection using vibration signal analysis
  publication-title: Sensors
– volume: 41
  start-page: 113
  year: 2013
  end-page: 126
  ident: b0430
  article-title: Feature extraction based on semi-supervised kernel marginal fisher analysis and its application in bearing fault diagnosis
  publication-title: Mechanical Systems and Signal Processing
– reference: (1), 31–42. 10.17531/ein.2017.1.5.
– volume: 5
  start-page: 6027
  year: 2017
  end-page: 6035
  ident: b0995
  article-title: Rolling element bearing fault diagnosis using improved manifold learning
  publication-title: IEEE Access
– reference: Li, Chuan. (n.d.). Gearbox fault diagnosis based on deep random forest fusion of acoustic and vibratory signals.
– volume: 22
  start-page: 1716
  year: 2008
  end-page: 1725
  ident: b0975
  article-title: Random forests classifier for machine fault diagnosis
  publication-title: Journal of Mechanical Science and Technology
– volume: 1–46
  year: 2022
  ident: b0635
  article-title: A review of cooperative multi-agent deep reinforcement learning
  publication-title: Applied Intelligence
– volume: 17
  start-page: 1947
  year: 2022
  end-page: 1959
  ident: b0085
  article-title: Unified Fault-Tolerant control for Air-Fuel ratio control of internal combustion engines with advanced analytical and hardware redundancies
  publication-title: Journal of Electrical Engineering & Technology
– volume: 578
  start-page: 887
  year: 2021
  end-page: 912
  ident: b0795
  article-title: Feature selection using fisher score and multilabel neighborhood rough sets for multilabel classification
  publication-title: Information Sciences
– volume: 107
  start-page: 241
  year: 2018
  end-page: 265
  ident: b0450
  article-title: A review on the application of deep learning in system health management
  publication-title: Mechanical Systems and Signal Processing
– volume: 105
  year: 2022
  ident: b0710
  article-title: Design of active fault-tolerant control system for air-fuel ratio control of internal combustion engines using fuzzy logic controller
  publication-title: Science Progress
– reference: , 1–5. Stevenson, WA: IEEE. 10.23919/WAC.2018.8430387.
– volume: 55
  start-page: 2378
  year: 2019
  end-page: 2391
  ident: b0025
  article-title: Machine Learning-Based fault diagnosis for single- and Multi-Faults in induction motors using measured stator currents and vibration signals
  publication-title: IEEE Transactions on Industry Applications
– volume: 67
  start-page: 2326
  year: 2020
  end-page: 2336
  ident: b0950
  article-title: An incorrect data detection method for big data cleaning of machinery condition monitoring
  publication-title: IEEE Transactions on Industrial Electronics
– reference: , 5622–5626. 10.1109/CCDC.2017.7978168.
– volume: 17
  start-page: 1729
  year: 2017
  ident: b0505
  article-title: An ensemble deep convolutional neural network model with improved d-S evidence fusion for bearing fault diagnosis
  publication-title: Sensors
– reference: Vanraj, Dhami, S., & Pabla, B. (2018). Hybrid data fusion approach for fault diagnosis of fixed-axis gearbox.
– volume: 100
  start-page: 358
  year: 2020
  end-page: 372
  ident: b0620
  article-title: Online aNN-based fault diagnosis implementation using an FPGA: Application in the EFI system of a vehicle
  publication-title: ISA Transactions
– volume: 15
  start-page: 2446
  year: 2019
  end-page: 2455
  ident: b0770
  article-title: Highly accurate machine fault diagnosis using deep transfer learning
  publication-title: IEEE Transactions on Industrial Informatics
– volume: 108
  start-page: 134
  year: 2018
  end-page: 142
  ident: b0135
  article-title: Bearing faults diagnosis using fuzzy expert system relying on an improved range overlaps and similarity method
  publication-title: Expert Systems with Applications
– volume: 20
  start-page: 470
  year: 2014
  end-page: 480
  ident: b0425
  article-title: Fault diagnosis of rolling bearings based on marginal fisher analysis
  publication-title: Journal of Vibration and Control
– volume: 161
  start-page: 168
  year: 2015
  end-page: 182
  ident: b0700
  article-title: Scalable extensions of the ReliefF algorithm for weighting and selecting features on the multi-label learning context
  publication-title: Neurocomputing
– volume: 92
  year: 2020
  ident: b0860
  article-title: A weighted corrective fuzzy reasoning spiking neural P system for fault diagnosis in power systems with variable topologies
  publication-title: Engineering Applications of Artificial Intelligence
– reference: Dong, L., Li, W., Wang, C.-H., & Lin, K.-P. (2020). Gyro motor fault classification model based on a coupled hidden Markov model with a minimum intra-class distance algorithm.
– volume: 21
  start-page: 3463
  year: 2021
  ident: b0125
  article-title: Wear diagnostics of the thrust bearing of NK-33 Turbo-Pump unit on the basis of Single-Coil eddy current sensors
  publication-title: Sensors
– start-page: 2200
  year: 2013
  end-page: 2207
  ident: b0555
  article-title: Transfer feature learning with joint distribution adaptation
  publication-title: 2013 IEEE International Conference on Computer Vision
– volume: 1–16
  year: 2021
  ident: b0080
  article-title: Robust passive fault tolerant control for air fuel ratio control of internal combustion gasoline engine for sensor and actuator faults
  publication-title: IETE Journal of Research
– volume: 46
  start-page: 259
  year: 2013
  end-page: 271
  ident: b0540
  article-title: Blind vibration component separation and nonlinear feature extraction applied to the nonstationary vibration signals for the gearbox multi-fault diagnosis
  publication-title: Measurement
– volume: 9
  start-page: 805
  year: 2022
  end-page: 825
  ident: b0630
  article-title: Feature selection algorithm based on density and distance for fault diagnosis applied to a roll-to-roll manufacturing system
  publication-title: Journal of Computational Design and Engineering
– volume: 8
  start-page: 1621
  year: 2018
  ident: b0415
  article-title: A fusion feature extraction method using EEMD and correlation coefficient analysis for bearing fault diagnosis
  publication-title: Applied Sciences
– volume: 26
  start-page: 83
  year: 2021
  end-page: 88
  ident: b0730
  article-title: Analysis of L2 regularization hyper parameter for stock price prediction
  publication-title: Journal of Institute of Science and Technology
– volume: 8
  start-page: 1859
  year: 2018
  ident: b0810
  article-title: Fault diagnosis of rolling bearings based on improved fast spectral correlation and optimized random forest
  publication-title: Applied Sciences
– volume: 15
  start-page: 5139
  year: 2019
  end-page: 5148
  ident: b0870
  article-title: A hierarchical deep domain adaptation approach for fault diagnosis of power plant thermal system
  publication-title: IEEE Transactions on Industrial Informatics
– volume: 43
  start-page: 18
  year: 2019
  ident: b0940
  article-title: Prediction of hemodialysis timing based on LVW feature selection and ensemble learning
  publication-title: Journal of Medical Systems
– volume: 79
  start-page: 65
  year: 2017
  end-page: 75
  ident: b0225
  article-title: Stability-based system for bearing fault early detection
  publication-title: Expert Systems with Applications
– reference: , 2208–2217. Sydney, NSW, Australia: JMLR.org.
– volume: 68
  start-page: 6248
  year: 2021
  end-page: 6256
  ident: b0780
  article-title: Fault diagnosis of an autonomous vehicle with an improved SVM algorithm subject to unbalanced datasets
  publication-title: IEEE Transactions on Industrial Electronics
– volume: 21
  start-page: 1727
  year: 2021
  end-page: 1734
  ident: b0195
  article-title: Infrared Thermography-Based fault diagnosis of induction motor bearings using machine learning
  publication-title: IEEE Sensors Journal
– volume: 23
  start-page: 1510
  year: 2021
  ident: b0715
  article-title: Bearing fault diagnosis using refined composite generalized multiscale dispersion Entropy-Based skewness and variance and multiclass FCM-ANFIS
  publication-title: Entropy
– volume: 35
  start-page: 1
  year: 2022
  end-page: 18
  ident: b1025
  article-title: A review on fault-tolerant cooperative control of multiple unmanned aerial vehicles
  publication-title: Chinese Journal of Aeronautics
– reference: .
– volume: 12
  year: 2020
  ident: b0020
  article-title: Reliable speed control of a permanent magnet DC motor using fault-tolerant h-bridge
  publication-title: Advances in Mechanical Engineering
– volume: 131
  start-page: 524
  year: 2019
  end-page: 533
  ident: b0790
  article-title: Faulty bearing detection, classification and location in a three-phase induction motor based on stockwell transform and support vector machine
  publication-title: Measurement
– volume: 10
  start-page: 131
  year: 2017
  ident: b1030
  article-title: A soft Sensor-Based Fault-Tolerant control on the air fuel ratio of Spark-Ignition engines
  publication-title: Energies
– volume: 319
  start-page: 155
  year: 2018
  end-page: 163
  ident: b0310
  article-title: A hybrid feature model and deep learning based fault diagnosis for unmanned aerial vehicle sensors
  publication-title: Neurocomputing
– volume: 53
  start-page: 3550
  year: 2015
  end-page: 3564
  ident: b0600
  article-title: Semisupervised transfer component analysis for domain adaptation in remote sensing image classification
  publication-title: IEEE Transactions on Geoscience and remote sensing
– volume: 272
  start-page: 619
  year: 2018
  end-page: 628
  ident: b0405
  article-title: A neural network constructed by deep learning technique and its application to intelligent fault diagnosis of machines
  publication-title: Neurocomputing
– volume: 69
  start-page: 187
  year: 2017
  end-page: 201
  ident: b0760
  article-title: Rolling bearing fault diagnosis using adaptive deep belief network with dual-tree complex wavelet packet
  publication-title: ISA Transactions
– volume: 255
  year: 2022
  ident: b0480
  article-title: Takagi-Sugeno fuzzy based power system fault section diagnosis models via genetic learning adaptive GSK algorithm
  publication-title: Knowledge-Based Systems
– volume: 48
  start-page: 34
  year: 2018
  end-page: 50
  ident: b1065
  article-title: Imbalanced data fault diagnosis of rotating machinery using synthetic oversampling and feature learning
  publication-title: Journal of Manufacturing Systems
– volume: 71
  start-page: 1
  year: 2022
  end-page: 11
  ident: b0090
  article-title: Interpretable neural network via algorithm unrolling for mechanical fault diagnosis
  publication-title: IEEE Transactions on Instrumentation and Measurement
– volume: 7
  start-page: 17634
  year: 2019
  end-page: 17643
  ident: b0065
  article-title: Advanced fault tolerant Air-Fuel ratio control of internal combustion gas engine for sensor and actuator faults
  publication-title: IEEE Access
– volume: 122
  start-page: 692
  year: 2019
  end-page: 706
  ident: b0970
  article-title: An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings
  publication-title: Mechanical Systems and Signal Processing
– volume: 144
  start-page: 65
  year: 2018
  end-page: 76
  ident: b0855
  article-title: Convolutional neural network-based hidden markov models for rolling element bearing fault identification
  publication-title: Knowledge-Based Systems
– volume: 1–11
  year: 2020
  ident: b0340
  article-title: active Fault-Tolerant control for discrete vehicle active suspension via Reduced-Order observer
  publication-title: IEEE Transactions on Systems, Man, and Cybernetics: Systems
– reference: Warde-Farley, D., & Xu, B. (2014). Generative adversarial nets.
– volume: 9
  start-page: 936
  year: 2015
  end-page: 944
  ident: b1000
  article-title: Planetary gearbox fault diagnostic method using acoustic emission sensors
  publication-title: IET Science, Measurement & Technology
– volume: 2
  year: 2022
  ident: b0675
  article-title: A review of feature selection methods for machine Learning-Based disease risk prediction
  publication-title: Frontiers in Bioinformatics
– volume: 48
  start-page: 6237
  year: 2023
  end-page: 6252
  ident: b0190
  article-title: Condition monitoring and fault diagnosis of induction motor using DWT and ANN
  publication-title: Arabian Journal for Science and Engineering
– volume: 66
  start-page: 7316
  year: 2019
  end-page: 7325
  ident: b0315
  article-title: Deep convolutional transfer learning network: A new method for intelligent fault diagnosis of machines with unlabeled data
  publication-title: IEEE Transactions on Industrial Electronics
– volume: 259
  start-page: 252
  year: 2014
  end-page: 268
  ident: b0365
  article-title: Bayesian classifiers based on probability density estimation and their applications to simultaneous fault diagnosis
  publication-title: Information Sciences
– volume: 143
  start-page: 58
  year: 2019
  end-page: 68
  ident: b0060
  article-title: A review of fault tolerant control systems: Advancements and applications
  publication-title: Measurement
– volume: 55
  start-page: 724
  year: 2022
  end-page: 729
  ident: b0900
  article-title: Fault-Tolerant control for a high altitude long endurance aircraft
  publication-title: IFAC-PapersOnLine
– start-page: 770
  year: 2016
  end-page: 778
  ident: b0360
  publication-title: Deep Residual Learning for Image Recognition
– year: 2018
  ident: b0500
  article-title: PSO optimized ANN diagnosis of early gear pitting
  publication-title: , 1043–1048
– start-page: 19
  year: 2013
  end-page: 42
  ident: b0265
  article-title: Dependability evaluation techniques
  publication-title: Fault-Tolerant Design
– volume: 34
  start-page: 117
  year: 2017
  end-page: 129
  ident: b0835
  article-title: Deep-Learning systems for domain adaptation in computer vision: Learning transferable feature representations
  publication-title: IEEE Signal Processing Magazine
– volume: 8
  start-page: 2885
  year: 2020
  end-page: 2892
  ident: b0840
  article-title: A novel resilient robot: Kinematic analysis and experimentation
  publication-title: IEEE Access
– reference: Research on Degradation State Recognition of Planetary Gear Based on Multiscale Information Dimension of SSD and CNN. (n.d.). Retrieved February 19, 2021, from https://www.hindawi.com/journals/complexity/2019/8716979/.
– volume: 2016
  start-page: 81
  year: 2016
  end-page: 86
  ident: b0845
  article-title: A factor analysis based transfer learning method for gearbox diagnosis under various operating conditions
  publication-title: International Symposium on Flexible Automation (ISFA)
– reference: Shi, P., Liang, K., Han, D., & Zhang, Y. (2017). A novel intelligent fault diagnosis method of rotating machinery based on deep learning and PSO-SVM.
– reference: (4), 936–945. 10.1177/1475921717727700.
– volume: 12
  start-page: 7841
  year: 2022
  ident: b0040
  article-title: A comparative study of design of active Fault-Tolerant control system for Air-Fuel ratio control of internal combustion engine using particle swarm optimization, genetic algorithm, and nonlinear Regression-Based observer model
  publication-title: Applied Sciences
– reference: , 35.
– volume: 20
  start-page: 1691
  year: 2017
  end-page: 1702
  ident: b0140
  article-title: A novel approach for marine diesel engine fault diagnosis
  publication-title: Cluster Computing
– volume: 22
  start-page: 6448
  year: 2022
  ident: b0010
  article-title: A centrifugal pump fault diagnosis framework based on supervised contrastive learning
  publication-title: Sensors
– reference: ,
– volume: 118
  start-page: 159
  year: 2021
  end-page: 173
  ident: b0850
  article-title: A bayesian inference-based approach for performance prognostics towards uncertainty quantification and its applications on the marine diesel engine
  publication-title: ISA Transactions
– volume: 35
  start-page: 242
  year: 2022
  end-page: 254
  ident: b0440
  article-title: An effective crack position diagnosis method for the hollow shaft rotor system based on the convolutional neural network and deep metric learning
  publication-title: Chinese Journal of Aeronautics
– volume: 10
  start-page: 245
  year: 2016
  end-page: 248
  ident: b1045
  article-title: Design theory and methodology for enterprise systems
  publication-title: Enterprise Information Systems
– volume: 106
  start-page: 142
  year: 2019
  end-page: 153
  ident: b0395
  article-title: Automated bearing fault diagnosis scheme using 2D representation of wavelet packet transform and deep convolutional neural network
  publication-title: Computers in Industry
– reference: , 35–40. 10.1109/SDPC.2018.8664814.
– volume: 521
  start-page: 436
  year: 2015
  end-page: 444
  ident: b0475
  article-title: Deep learning
  publication-title: Nature
– volume: 49
  start-page: 136
  year: 2019
  end-page: 144
  ident: b0910
  article-title: A new deep transfer learning based on sparse Auto-Encoder for fault diagnosis
  publication-title: IEEE Transactions on Systems, Man, and Cybernetics: Systems
– reference: Safizadeh, M. S., & Yari, B. (2017). Pump cavitation detection through fusion of support vector machine classifier data associated with vibration and motor current signature. 59(12), 5.
– reference: Gerdes, M., Galar, D., & Scholz, D. (2016). Decision trees and the effects of feature extraction parameters for robust sensor network design.
– volume: 51
  start-page: 309
  year: 2018
  end-page: 314
  ident: b0945
  article-title: A platform for fault diagnosis of High-Speed train based on big data
  publication-title: IFAC-PapersOnLine
– volume: 139
  year: 2020
  ident: b0370
  article-title: A general anomaly detection framework for fleet-based condition monitoring of machines
  publication-title: Mechanical Systems and Signal Processing
– volume: 39
  start-page: 1000
  year: 2017
  end-page: 1006
  ident: b0095
  article-title: Application of variational mode decomposition energy distribution to bearing fault diagnosis in a wind turbine
  publication-title: Transactions of the Institute of Measurement and Control
– volume: 166
  year: 2021
  ident: b0235
  article-title: Machine learning and data mining in manufacturing
  publication-title: Expert Systems with Applications
– volume: 32
  start-page: 75
  year: 2019
  ident: b0205
  article-title: Signal-Based intelligent hydraulic fault diagnosis methods: Review and prospects
  publication-title: Chinese Journal of Mechanical Engineering
– volume: 32
  start-page: 37
  year: 2018
  end-page: 47
  ident: b1010
  article-title: Fault diagnosis of planetary gearbox with incomplete information using assignment reduction and flexible naive bayesian classifier
  publication-title: Journal of Mechanical Science and Technology
– volume: 4
  start-page: 99
  year: 2010
  end-page: 110
  ident: b1040
  article-title: On the principle of design of resilient systems – application to enterprise information systems
  publication-title: Enterprise Information Systems
– start-page: 2397
  year: 2005
  end-page: 2402
  ident: b0495
  article-title: Reliability modeling of fault tolerant control systems
  publication-title: Proceedings of the 44th IEEE Conference on Decision and control
– volume: 9
  start-page: 152616
  year: 2021
  end-page: 152627
  ident: b0460
  article-title: KNN-SC: Novel spectral clustering algorithm using k-Nearest neighbors
  publication-title: IEEE Access
– reference: (12), 125002. 10.1088/1361-6501/aae5b2.
– volume: 34
  start-page: 3451
  year: 2018
  end-page: 3462
  ident: b0670
  article-title: Feature engineering based on ANOVA, cluster validity assessment and KNN for fault diagnosis in bearings
  publication-title: Journal of Intelligent & Fuzzy Systems
– start-page: 179
  year: 2021
  end-page: 200
  ident: b0960
  article-title: Machine learning in expert systems for disease diagnostics in human healthcare
  publication-title: Machine Learning, Big Data, and IoT for Medical Informatics
– volume: 15
  start-page: 7010
  year: 2022
  ident: b0045
  article-title: Hybrid Fault-Tolerant control for Air-Fuel ratio control system of internal combustion engine using fuzzy logic and Super-Twisting sliding mode control techniques
  publication-title: Energies
– volume: 33
  start-page: 505
  year: 2019
  end-page: 511
  ident: b0305
  article-title: Fault diagnosis of rolling element bearing based on artificial neural network
  publication-title: Journal of Mechanical Science and Technology
– volume: 11
  start-page: 2057
  year: 2023
  end-page: 2067
  ident: b0100
  article-title: Fault diagnosis of a centrifugal pump using electrical signature analysis and support vector machine
  publication-title: Journal of Vibration Engineering & Technologies
– volume: 22
  start-page: 1345
  year: 2010
  end-page: 1359
  ident: b0640
  article-title: A survey on transfer learning
  publication-title: IEEE Transactions on Knowledge and Data Engineering
– volume: 18
  start-page: 1
  year: 2014
  end-page: 8
  ident: b0720
  article-title: Using multi-sensor data fusion for vibration fault diagnosis of rolling element bearings by accelerometer and load cell
  publication-title: Information Fusion
– volume: 165
  start-page: 474
  year: 2019
  end-page: 487
  ident: b0345
  article-title: A novel adversarial learning framework in deep convolutional neural network for intelligent diagnosis of mechanical faults
  publication-title: Knowledge-Based Systems
– volume: 69
  start-page: 9485
  year: 2020
  end-page: 9495
  ident: b0865
  article-title: Active fault tolerant control for unmanned underwater vehicle with sensor faults
  publication-title: IEEE Transactions on Instrumentation and Measurement
– volume: 93
  start-page: 175
  year: 2017
  end-page: 203
  ident: b0580
  article-title: GNAR-GARCH model and its application in feature extraction for rolling bearing fault diagnosis
  publication-title: Mechanical Systems and Signal Processing
– volume: 7
  start-page: 19990
  year: 2019
  end-page: 19999
  ident: b0955
  article-title: A Digital-Twin-Assisted fault diagnosis using deep transfer learning
  publication-title: IEEE Access
– volume: 27
  start-page: 2140
  year: 2019
  end-page: 2151
  ident: b0705
  article-title: Intuitionistic fuzzy twin support vector machines
  publication-title: IEEE Transactions on fuzzy Systems
– volume: 99
  start-page: 14
  year: 2016
  ident: b0550
  article-title: Deep learning of transferable representation for scalable domain adaptation
  publication-title: IEEE Transactions on Knowledge and Data Engineering
– volume: 230
  start-page: 303
  year: 2016
  end-page: 313
  ident: b1020
  article-title: Combined flow graphs and normal naive bayesian classifier for fault diagnosis of gear box
  publication-title: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
– volume: 38
  start-page: 2255
  year: 2016
  end-page: 2263
  ident: b0250
  article-title: Application of fuzzy c-means method and classification model of optimized k-nearest neighbor for fault diagnosis of bearing
  publication-title: Journal of the Brazilian Society of Mechanical Sciences and Engineering
– volume: 18
  start-page: 4460
  year: 2018
  ident: b0410
  article-title: Symbolic important point perceptually and hidden markov model based hydraulic pump fault diagnosis method
  publication-title: Sensors
– volume: 95
  start-page: 295
  year: 2019
  end-page: 305
  ident: b1060
  article-title: Deep residual learning-based fault diagnosis method for rotating machinery
  publication-title: ISA Transactions
– reference: Savchynskyy, B. (2019).
– reference: , 11.
– volume: 66
  start-page: 1926
  year: 2017
  end-page: 1935
  ident: b0230
  article-title: Energy-Fluctuated multiscale feature learning with deep ConvNet for intelligent spindle bearing fault diagnosis
  publication-title: IEEE Transactions on Instrumentation and Measurement
– volume: 91
  start-page: 295
  year: 2017
  end-page: 312
  ident: b0530
  article-title: A fault diagnosis scheme for planetary gearboxes using modified multi-scale symbolic dynamic entropy and mRMR feature selection
  publication-title: Mechanical Systems and Signal Processing
– year: 2016
  ident: b0295
  article-title: Deep learning
– volume: 51
  start-page: 470
  year: 2018
  end-page: 475
  ident: b0375
  article-title: Fault detection and classification using artificial neural networks
  publication-title: IFAC-PapersOnLine
– reference: Chen, C., Li, Z., Yang, J., & Liang, B. (2017). A cross domain feature extraction method based on transfer component analysis for rolling bearing fault diagnosis.
– volume: 96
  start-page: 803
  year: 2018
  end-page: 819
  ident: b0260
  article-title: Development and trend of condition monitoring and fault diagnosis of multi-sensors information fusion for rolling bearings: A review
  publication-title: The International Journal of Advanced Manufacturing Technology
– volume: 66–67
  start-page: 679
  year: 2016
  end-page: 698
  ident: b0875
  article-title: Spectral kurtosis for fault detection, diagnosis and prognostics of rotating machines: A review with applications
  publication-title: Mechanical Systems and Signal Processing
– volume: 15
  start-page: 583
  year: 2016
  end-page: 598
  ident: b0455
  article-title: Fault detection of engine timing belt based on vibration signals using data-mining techniques and a novel data fusion procedure
  publication-title: Structural Health Monitoring
– reference: (8), 5932–5946. 10.21595/jve.2017.18380.
– reference: (n/a). 10.1111/risa.14089.
– year: 2013
  ident: b0605
  article-title: Big data: A revolution that will transform how we live, work, and think
– volume: 12
  start-page: 2941
  year: 2000
  end-page: 2964
  ident: b0130
  article-title: A quantitative study of fault tolerance, noise immunity, and generalization ability of MLPs
  publication-title: Neural Computation
– volume: 25
  start-page: 1880
  year: 2018
  end-page: 1884
  ident: b1005
  article-title: Multiscale representations fusion with joint multiple reconstructions autoencoder for intelligent fault diagnosis
  publication-title: IEEE Signal Processing Letters
– reference: (B. Curless, W. T. Freeman, & L. V. Gool, Eds.). Boston Delft: Now.
– reference: Saufi, S. R., Ahmad, Z. A. bin, Leong, M. S., & Lim, M. H. (2018). Differential evolution optimization for resilient stacked sparse autoencoder and its applications on bearing fault diagnosis.
– volume: 6
  start-page: 63584
  year: 2018
  end-page: 63596
  ident: b0925
  article-title: An End-to-End model based on improved adaptive deep belief network and its application to bearing fault diagnosis
  publication-title: IEEE Access
– volume: 52
  start-page: 473
  year: 2019
  end-page: 492
  ident: b0070
  article-title: Hybrid fault tolerant control for air–fuel ratio control of internal combustion gasoline engine using kalman filters with advanced redundancy
  publication-title: Measurement and Control
– volume: 6
  start-page: 980
  year: 2015
  end-page: 987
  ident: b0110
  article-title: An artificial neural network approach for early fault detection of gearbox bearings
  publication-title: IEEE Transactions on Smart Grid
– volume: 63
  start-page: 2651
  year: 2014
  end-page: 2665
  ident: b0510
  article-title: Fault detection and classification in medium voltage DC shipboard power systems with wavelets and artificial neural networks
  publication-title: IEEE Transactions on Instrumentation and Measurement
– volume: 28
  start-page: 04014065
  year: 2015
  ident: b0885
  article-title: Fault early recognition and health monitoring on aeroengine rotor system
  publication-title: Journal of Aerospace Engineering
– volume: 6
  start-page: 26241
  year: 2018
  end-page: 26253
  ident: b0145
  article-title: Preprocessing-Free gear fault diagnosis using small datasets with deep convolutional neural Network-Based transfer learning
  publication-title: IEEE Access
– volume: 127
  start-page: 246
  year: 2018
  end-page: 255
  ident: b0350
  article-title: Multi-level wavelet packet fusion in dynamic ensemble convolutional neural network for fault diagnosis
  publication-title: Measurement
– volume: 12
  start-page: 1
  year: 2018
  end-page: 18
  ident: b0470
  article-title: Reliability analysis of safety-critical and control systems: A state-of-the-art review
  publication-title: IET Software
– volume: 85
  start-page: 189
  year: 2018
  end-page: 203
  ident: b0820
  article-title: Relief-based feature selection: Introduction and review
  publication-title: Journal of Biomedical Informatics
– volume: 127
  start-page: 190
  year: 2019
  end-page: 201
  ident: b0590
  article-title: Deep residual learning with demodulated time-frequency features for fault diagnosis of planetary gearbox under nonstationary running conditions
  publication-title: Mechanical Systems and Signal Processing
– volume: 230
  start-page: 291
  year: 2016
  end-page: 302
  ident: b0825
  article-title: Two-stage feature selection for bearing fault diagnosis based on dual-tree complex wavelet transform and empirical mode decomposition
  publication-title: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
– reference: Chen, Jinglong. (n.d.). Wavelet transform based on inner product in fault diagnosis of rotating machinery_A review.
– reference: Yang, B., Lei, Y., Jia, F., & Xing, S. (2018). A Transfer Learning Method for Intelligent Fault Diagnosis from Laboratory Machines to Real-Case Machines.
– volume: 310
  start-page: 77
  year: 2018
  end-page: 95
  ident: b0520
  article-title: A robust intelligent fault diagnosis method for rolling element bearings based on deep distance metric learning
  publication-title: Neurocomputing
– volume: 65
  start-page: 4290
  year: 2018
  end-page: 4300
  ident: b1070
  article-title: Deep residual networks with dynamically weighted wavelet coefficients for fault diagnosis of planetary gearboxes
  publication-title: IEEE Transactions on Industrial Electronics
– volume: 15
  year: 2023
  ident: b0755
  article-title: Design of hybrid fault-tolerant control system for air-fuel ratio control of internal combustion engines using artificial neural network and sliding mode control against sensor faults
  publication-title: Advances in Mechanical Engineering
– volume: 85
  start-page: 56
  year: 2017
  end-page: 70
  ident: b0105
  article-title: Diagnosis of combined faults in rotary machinery by Non-Naive bayesian approach
  publication-title: Mechanical Systems and Signal Processing
– volume: 60
  start-page: 84
  year: 2017
  end-page: 90
  ident: b0465
  article-title: ImageNet classification with deep convolutional neural networks
  publication-title: Communications of the ACM
– volume: Vol. 52
  start-page: 1879
  year: 2023
  end-page: 1884
  ident: b0610
  article-title: Artificial neural networks-based identification of the WWTP DO sensor types of faults
  publication-title: Computer Aided Chemical Engineering
– volume: 2018
  start-page: 1309
  year: 2018
  end-page: 1313
  ident: b0935
  article-title: A transfer learning strategy for rotation machinery fault diagnosis based on Cycle-Consistent generative adversarial networks
  publication-title: Chinese Automation Congress (CAC)
– reference: H. Saltzer, J., & Kaashoek, M. F. (2021, August 1). 2.3: Measures of Reliability and Failure Tolerance. Retrieved August 23, 2023, from Engineering LibreTexts website: https://eng.libretexts.org/Bookshelves/Computer_Science/Programming_and_Computation_Fundamentals/Principles_of_Computer_System_Design_(Saltzer_and_Kaashoek)/02%3A_Fault_Tolerance_-_Reliable_Systems_from_Unreliable_Components/2.03%3A_Measures_of_Reliability_and_Failure_Tolerance.
– volume: 9
  start-page: 494
  year: 2018
  end-page: 508
  ident: b0400
  article-title: fault diagnosis of automobile systems using fault tree based on digraph modeling
  publication-title: International Journal of System Assurance Engineering and Management
– reference: Long, M., Zhu, H., Wang, J., & Jordan, M. I. (2017). Deep transfer learning with joint adaptation networks.
– volume: 4
  start-page: 217
  year: 2013
  end-page: 233
  ident: b0120
  article-title: Parameter selection algorithm with self adaptive growing neural network classifier for diagnosis issues
  publication-title: International Journal of Machine Learning and Cybernetics
– start-page: 1
  year: 2016
  end-page: 5
  ident: b0005
  article-title: Reliability enhancement of modular multilevel converter by applying fault tolerant control
  publication-title: 2016 51st International Universities Power Engineering Conference (UPEC)
– volume: 198
  year: 2019
  ident: b0185
  article-title: Deep residual network based fault detection and diagnosis of photovoltaic arrays using current-voltage curves and ambient conditions
  publication-title: Energy Conversion and Management
– start-page: 1
  year: 2015
  end-page: 6
  ident: b0270
  publication-title: Bearing fault diagnosis based on SVD feature extraction and transfer learning classification
– reference: Machine learning, explained. (n.d.). Retrieved December 20, 2022, from MIT Sloan website: https://mitsloan.mit.edu/ideas-made-to-matter/machine-learning-explained.
– volume: 90
  start-page: 219
  year: 2015
  end-page: 229
  ident: b0980
  article-title: Gear fault diagnosis based on support vector machine optimized by artificial bee colony algorithm
  publication-title: Mechanism and Machine Theory
– reference: Zhang, W. J., Yang, G., Lin, Y., Ji, C., & Gupta, M. M. (2018). On Definition of Deep Learning.
– volume: 66
  start-page: 3196
  year: 2019
  end-page: 3207
  ident: b0420
  article-title: Multiscale convolutional neural networks for fault diagnosis of wind turbine gearbox
  publication-title: IEEE Transactions on Industrial Electronics
– reference: (4th Edition edition). TMH.
– volume: 95
  start-page: 187
  year: 2017
  end-page: 204
  ident: b0765
  article-title: A novel deep autoencoder feature learning method for rotating machinery fault diagnosis
  publication-title: Mechanical Systems and Signal Processing
– volume: 9
  start-page: 379
  year: 2016
  ident: b0990
  article-title: Representational learning for fault diagnosis of wind turbine equipment: A Multi-Layered extreme learning machines approach
  publication-title: Energies
– volume: 229
  start-page: 304
  year: 2015
  end-page: 315
  ident: b0545
  article-title: Condition monitoring and fault diagnosis of diesel engines using instantaneous angular speed analysis
  publication-title: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
– reference: Deep Learning Enabled Fault Diagnosis Using Time-Frequency Image Analysis of Rolling Element Bearings. (n.d.). Retrieved February 19, 2021, from https://www.hindawi.com/journals/sv/2017/5067651/.
– volume: 66
  start-page: 5525
  year: 2019
  end-page: 5534
  ident: b0515
  article-title: Cross-Domain fault diagnosis of rolling element bearings using deep generative neural networks
  publication-title: IEEE Transactions on Industrial Electronics
– volume: 170
  year: 2021
  ident: b0625
  article-title: New bearing slight degradation detection approach based on the periodicity intensity factor and signal processing methods
  publication-title: Measurement
– volume: 7
  start-page: 41
  year: 2017
  ident: b0320
  article-title: Deep fault recognizer: an integrated model to denoise and extract features for fault diagnosis in rotating machinery
  publication-title: Applied Sciences
– volume: 66
  start-page: 4696
  year: 2019
  end-page: 4706
  ident: b1075
  article-title: Multiple wavelet coefficients fusion in deep residual networks for fault diagnosis
  publication-title: IEEE Transactions on Industrial Electronics
– reference: Li, G., Gu, Y., & Ding, J. (2020, October 2).
– reference: (5), 646–661. 10.1177/0959651819866281.
– volume: 122
  start-page: 502
  year: 2019
  end-page: 536
  ident: b0680
  article-title: Applications of stochastic resonance to machinery fault detection: A review and tutorial
  publication-title: Mechanical Systems and Signal Processing
– volume: 51
  start-page: 4091
  year: 2021
  end-page: 4101
  ident: b1035
  article-title: Neural Networks-Based fault tolerant control of a robot via fast terminal sliding mode
  publication-title: IEEE Transactions on Systems, Man, and Cybernetics: Systems
– volume: 69
  start-page: 187
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0760
  article-title: Rolling bearing fault diagnosis using adaptive deep belief network with dual-tree complex wavelet packet
  publication-title: ISA Transactions
  doi: 10.1016/j.isatra.2017.03.017
– year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0500
  article-title: PSO optimized ANN diagnosis of early gear pitting
– volume: 99
  start-page: 14
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b0550
  article-title: Deep learning of transferable representation for scalable domain adaptation
  publication-title: IEEE Transactions on Knowledge and Data Engineering
– volume: 35
  start-page: 1
  issue: 1
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b1025
  article-title: A review on fault-tolerant cooperative control of multiple unmanned aerial vehicles
  publication-title: Chinese Journal of Aeronautics
  doi: 10.1016/j.cja.2021.04.022
– volume: 23
  start-page: 1510
  issue: 11
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0715
  article-title: Bearing fault diagnosis using refined composite generalized multiscale dispersion Entropy-Based skewness and variance and multiclass FCM-ANFIS
  publication-title: Entropy
  doi: 10.3390/e23111510
– volume: 61
  start-page: 85
  year: 2015
  ident: 10.1016/j.eswa.2023.121956_b0745
  article-title: Deep learning in neural networks: an overview
  publication-title: Neural Networks
  doi: 10.1016/j.neunet.2014.09.003
– volume: 315
  start-page: 447
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b1085
  article-title: Fault diagnosis of rolling bearing based on feature reduction with global-local margin fisher analysis
  publication-title: Neurocomputing
  doi: 10.1016/j.neucom.2018.07.038
– volume: 1–46
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0635
  article-title: A review of cooperative multi-agent deep reinforcement learning
  publication-title: Applied Intelligence
– volume: 379
  start-page: 20200371
  issue: 2207
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0170
  article-title: Stochastic model predictive control framework for resilient cyber-physical systems: Review and perspectives
  publication-title: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
  doi: 10.1098/rsta.2020.0371
– ident: 10.1016/j.eswa.2023.121956_b0165
  doi: 10.1109/CCDC.2017.7978168
– volume: 176
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0200
  article-title: Convolutional neural network based bearing fault diagnosis of rotating machine using thermal images
  publication-title: Measurement
  doi: 10.1016/j.measurement.2021.109196
– volume: 34
  issue: 9
  year: 2023
  ident: 10.1016/j.eswa.2023.121956_b0920
  article-title: Intelligent fault diagnosis of gear crack based on side frequency feature under different working conditions
  publication-title: Measurement Science and Technology
  doi: 10.1088/1361-6501/acd9df
– volume: 105
  issue: 2
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0710
  article-title: Design of active fault-tolerant control system for air-fuel ratio control of internal combustion engines using fuzzy logic controller
  publication-title: Science Progress
  doi: 10.1177/00368504221094723
– volume: 10
  start-page: 131
  issue: 1
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b1030
  article-title: A soft Sensor-Based Fault-Tolerant control on the air fuel ratio of Spark-Ignition engines
  publication-title: Energies
  doi: 10.3390/en10010131
– volume: 17
  start-page: e0279101
  issue: 12
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0035
  article-title: Design of active Fault-Tolerant control system for Air-Fuel ratio control of internal combustion engine using nonlinear regression-based observer model
  publication-title: PLoS One1
  doi: 10.1371/journal.pone.0279101
– volume: 139
  year: 2020
  ident: 10.1016/j.eswa.2023.121956_b0370
  article-title: A general anomaly detection framework for fleet-based condition monitoring of machines
  publication-title: Mechanical Systems and Signal Processing
  doi: 10.1016/j.ymssp.2019.106585
– volume: 15
  start-page: 583
  issue: 5
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b0455
  article-title: Fault detection of engine timing belt based on vibration signals using data-mining techniques and a novel data fusion procedure
  publication-title: Structural Health Monitoring
  doi: 10.1177/1475921716652582
– volume: 67
  start-page: 1293
  issue: 2
  year: 2020
  ident: 10.1016/j.eswa.2023.121956_b1095
  article-title: Intelligent fault identification based on multisource domain generalization towards actual diagnosis scenario
  publication-title: IEEE Transactions on Industrial Electronics
  doi: 10.1109/TIE.2019.2898619
– volume: 122
  start-page: 692
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0970
  article-title: An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings
  publication-title: Mechanical Systems and Signal Processing
  doi: 10.1016/j.ymssp.2018.12.051
– volume: 15
  start-page: 7010
  issue: 19
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0045
  article-title: Hybrid Fault-Tolerant control for Air-Fuel ratio control system of internal combustion engine using fuzzy logic and Super-Twisting sliding mode control techniques
  publication-title: Energies
  doi: 10.3390/en15197010
– volume: 71
  start-page: 1
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0090
  article-title: Interpretable neural network via algorithm unrolling for mechanical fault diagnosis
  publication-title: IEEE Transactions on Instrumentation and Measurement
– ident: 10.1016/j.eswa.2023.121956_b0895
– volume: 20
  start-page: 470
  issue: 3
  year: 2014
  ident: 10.1016/j.eswa.2023.121956_b0425
  article-title: Fault diagnosis of rolling bearings based on marginal fisher analysis
  publication-title: Journal of Vibration and Control
  doi: 10.1177/1077546312463747
– volume: 20
  start-page: 932
  issue: 12
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0650
  article-title: Rotor fault diagnosis based on characteristic frequency band energy entropy and support vector machine
  publication-title: Entropy
  doi: 10.3390/e20120932
– ident: 10.1016/j.eswa.2023.121956_b0735
  doi: 10.1088/1361-6501/aae5b2
– volume: 90
  start-page: 219
  year: 2015
  ident: 10.1016/j.eswa.2023.121956_b0980
  article-title: Gear fault diagnosis based on support vector machine optimized by artificial bee colony algorithm
  publication-title: Mechanism and Machine Theory
  doi: 10.1016/j.mechmachtheory.2015.03.013
– volume: 96
  start-page: 289
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b0690
  article-title: A review on signal processing techniques utilized in the fault diagnosis of rolling element bearings
  publication-title: Tribology international
  doi: 10.1016/j.triboint.2015.12.037
– volume: 36
  start-page: 354
  issue: 4
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0245
  article-title: Fault diagnosis of bearing based on the Kernel principal component analysis and optimized k -nearest neighbour model
  publication-title: Journal of Low Frequency Noise, Vibration and Active Control
  doi: 10.1177/1461348417744302
– volume: 310
  start-page: 77
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0520
  article-title: A robust intelligent fault diagnosis method for rolling element bearings based on deep distance metric learning
  publication-title: Neurocomputing
  doi: 10.1016/j.neucom.2018.05.021
– volume: 100
  start-page: 439
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b1055
  article-title: A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load
  publication-title: Mechanical Systems and Signal Processing
  doi: 10.1016/j.ymssp.2017.06.022
– volume: 55
  start-page: 703
  issue: 7–8
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0390
  article-title: Genetic algorithm based active fault-tolerant control system for air fuel ratio control of internal combustion engines
  publication-title: Measurement and Control
  doi: 10.1177/00202940221115233
– volume: 109
  start-page: 85
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b1090
  article-title: Artificial intelligence-based fault detection and diagnosis methods for building energy systems: Advantages, challenges and the future
  publication-title: Renewable and Sustainable Energy Reviews
  doi: 10.1016/j.rser.2019.04.021
– volume: 48
  start-page: 6237
  issue: 5
  year: 2023
  ident: 10.1016/j.eswa.2023.121956_b0190
  article-title: Condition monitoring and fault diagnosis of induction motor using DWT and ANN
  publication-title: Arabian Journal for Science and Engineering
  doi: 10.1007/s13369-022-07294-3
– volume: 32
  start-page: 139
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0565
  article-title: Intelligent fault diagnosis of rolling bearing using hierarchical convolutional network based health state classification
  publication-title: Advanced Engineering Informatics
  doi: 10.1016/j.aei.2017.02.005
– volume: 18
  start-page: 1
  year: 2014
  ident: 10.1016/j.eswa.2023.121956_b0720
  article-title: Using multi-sensor data fusion for vibration fault diagnosis of rolling element bearings by accelerometer and load cell
  publication-title: Information Fusion
  doi: 10.1016/j.inffus.2013.10.002
– volume: 22
  start-page: 1716
  issue: 9
  year: 2008
  ident: 10.1016/j.eswa.2023.121956_b0975
  article-title: Random forests classifier for machine fault diagnosis
  publication-title: Journal of Mechanical Science and Technology
  doi: 10.1007/s12206-008-0603-6
– volume: 100
  start-page: 358
  year: 2020
  ident: 10.1016/j.eswa.2023.121956_b0620
  article-title: Online aNN-based fault diagnosis implementation using an FPGA: Application in the EFI system of a vehicle
  publication-title: ISA Transactions
  doi: 10.1016/j.isatra.2019.11.003
– volume: 165
  start-page: 474
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0345
  article-title: A novel adversarial learning framework in deep convolutional neural network for intelligent diagnosis of mechanical faults
  publication-title: Knowledge-Based Systems
  doi: 10.1016/j.knosys.2018.12.019
– volume: 7
  start-page: 19990
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0955
  article-title: A Digital-Twin-Assisted fault diagnosis using deep transfer learning
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2018.2890566
– ident: 10.1016/j.eswa.2023.121956_b0665
– volume: 11
  start-page: 2057
  issue: 5
  year: 2023
  ident: 10.1016/j.eswa.2023.121956_b0100
  article-title: Fault diagnosis of a centrifugal pump using electrical signature analysis and support vector machine
  publication-title: Journal of Vibration Engineering & Technologies
  doi: 10.1007/s42417-022-00687-6
– volume: 121
  start-page: 150
  year: 2013
  ident: 10.1016/j.eswa.2023.121956_b0285
  article-title: Comparison of FDA-based and PCA-based features in fault diagnosis of automobile gearboxes
  publication-title: Neurocomputing
  doi: 10.1016/j.neucom.2013.04.033
– volume: 85
  start-page: 189
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0820
  article-title: Relief-based feature selection: Introduction and review
  publication-title: Journal of Biomedical Informatics
  doi: 10.1016/j.jbi.2018.07.014
– volume: 98
  start-page: 114
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b0525
  article-title: Hierarchical fuzzy entropy and improved support vector machine based binary tree approach for rolling bearing fault diagnosis
  publication-title: Mechanism and Machine Theory
  doi: 10.1016/j.mechmachtheory.2015.11.010
– volume: 1–11
  year: 2020
  ident: 10.1016/j.eswa.2023.121956_b0340
  article-title: active Fault-Tolerant control for discrete vehicle active suspension via Reduced-Order observer
  publication-title: IEEE Transactions on Systems, Man, and Cybernetics: Systems
– year: 2013
  ident: 10.1016/j.eswa.2023.121956_b0605
– volume: 15
  issue: 3
  year: 2023
  ident: 10.1016/j.eswa.2023.121956_b0755
  article-title: Design of hybrid fault-tolerant control system for air-fuel ratio control of internal combustion engines using artificial neural network and sliding mode control against sensor faults
  publication-title: Advances in Mechanical Engineering
  doi: 10.1177/16878132231160729
– volume: 92
  year: 2020
  ident: 10.1016/j.eswa.2023.121956_b0860
  article-title: A weighted corrective fuzzy reasoning spiking neural P system for fault diagnosis in power systems with variable topologies
  publication-title: Engineering Applications of Artificial Intelligence
  doi: 10.1016/j.engappai.2020.103680
– volume: 9
  start-page: 805
  issue: 2
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0630
  article-title: Feature selection algorithm based on density and distance for fault diagnosis applied to a roll-to-roll manufacturing system
  publication-title: Journal of Computational Design and Engineering
  doi: 10.1093/jcde/qwac028
– volume: 46
  start-page: 1250
  issue: 3
  year: 2013
  ident: 10.1016/j.eswa.2023.121956_b0055
  article-title: Exploiting sound signals for fault diagnosis of bearings using decision tree
  publication-title: Measurement
  doi: 10.1016/j.measurement.2012.11.011
– volume: 12
  issue: 10
  year: 2020
  ident: 10.1016/j.eswa.2023.121956_b0020
  article-title: Reliable speed control of a permanent magnet DC motor using fault-tolerant h-bridge
  publication-title: Advances in Mechanical Engineering
  doi: 10.1177/1687814020970311
– volume: 6
  start-page: 980
  issue: 2
  year: 2015
  ident: 10.1016/j.eswa.2023.121956_b0110
  article-title: An artificial neural network approach for early fault detection of gearbox bearings
  publication-title: IEEE Transactions on Smart Grid
  doi: 10.1109/TSG.2014.2386305
– volume: 521
  start-page: 436
  issue: 7553
  year: 2015
  ident: 10.1016/j.eswa.2023.121956_b0475
  article-title: Deep learning
  publication-title: Nature
  doi: 10.1038/nature14539
– volume: 143
  start-page: 58
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0060
  article-title: A review of fault tolerant control systems: Advancements and applications
  publication-title: Measurement
  doi: 10.1016/j.measurement.2019.04.083
– volume: 21
  start-page: 7587
  issue: 22
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0445
  article-title: An expert system for rotating machine fault detection using vibration signal analysis
  publication-title: Sensors
  doi: 10.3390/s21227587
– volume: 95
  start-page: 295
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b1060
  article-title: Deep residual learning-based fault diagnosis method for rotating machinery
  publication-title: ISA Transactions
  doi: 10.1016/j.isatra.2018.12.025
– ident: 10.1016/j.eswa.2023.121956_b0965
  doi: 10.1109/SDPC.2018.8664814
– ident: 10.1016/j.eswa.2023.121956_b0490
– volume: 17
  start-page: 5581
  issue: 17
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0890
  article-title: Fault diagnosis of a rolling bearing using wavelet packet denoising and random forests
  publication-title: IEEE Sensors Journal
  doi: 10.1109/JSEN.2017.2726011
– volume: 46
  start-page: 259
  issue: 1
  year: 2013
  ident: 10.1016/j.eswa.2023.121956_b0540
  article-title: Blind vibration component separation and nonlinear feature extraction applied to the nonstationary vibration signals for the gearbox multi-fault diagnosis
  publication-title: Measurement
  doi: 10.1016/j.measurement.2012.06.013
– volume: 55
  start-page: 2378
  issue: 3
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0025
  article-title: Machine Learning-Based fault diagnosis for single- and Multi-Faults in induction motors using measured stator currents and vibration signals
  publication-title: IEEE Transactions on Industry Applications
  doi: 10.1109/TIA.2019.2895797
– volume: 22
  start-page: 199
  issue: 2
  year: 2011
  ident: 10.1016/j.eswa.2023.121956_b0645
  article-title: Domain adaptation via transfer component analysis
  publication-title: IEEE Transactions on Neural Networks
  doi: 10.1109/TNN.2010.2091281
– volume: 2016
  start-page: 81
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b0845
  article-title: A factor analysis based transfer learning method for gearbox diagnosis under various operating conditions
  publication-title: International Symposium on Flexible Automation (ISFA)
  doi: 10.1109/ISFA.2016.7790140
– volume: 9
  start-page: 936
  issue: 8
  year: 2015
  ident: 10.1016/j.eswa.2023.121956_b1000
  article-title: Planetary gearbox fault diagnostic method using acoustic emission sensors
  publication-title: IET Science, Measurement & Technology
  doi: 10.1049/iet-smt.2014.0375
– volume: 16
  start-page: 1969
  issue: 12
  year: 2023
  ident: 10.1016/j.eswa.2023.121956_b0255
  article-title: Passive fault-tolerant control for discrete parameter system
  publication-title: IET Power Electronics
  doi: 10.1049/pel2.12515
– volume: 10
  start-page: 2042
  issue: 2
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0660
  article-title: increasing feasibility of neural Network-Based early fault detection in induction motor drives
  publication-title: IEEE Journal of Emerging and Selected Topics in Power Electronics
  doi: 10.1109/JESTPE.2021.3115170
– volume: 52
  start-page: 1179
  issue: 9–10
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0075
  article-title: Robust active fault-tolerant control for internal combustion gas engine for air–fuel ratio control with statistical regression-based observer model
  publication-title: Measurement and Control
  doi: 10.1177/0020294018823031
– volume: 93
  start-page: 175
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0580
  article-title: GNAR-GARCH model and its application in feature extraction for rolling bearing fault diagnosis
  publication-title: Mechanical Systems and Signal Processing
  doi: 10.1016/j.ymssp.2017.01.043
– volume: 34
  start-page: 117
  issue: 6
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0835
  article-title: Deep-Learning systems for domain adaptation in computer vision: Learning transferable feature representations
  publication-title: IEEE Signal Processing Magazine
  doi: 10.1109/MSP.2017.2740460
– volume: 21
  start-page: 3463
  issue: 10
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0125
  article-title: Wear diagnostics of the thrust bearing of NK-33 Turbo-Pump unit on the basis of Single-Coil eddy current sensors
  publication-title: Sensors
  doi: 10.3390/s21103463
– volume: 166
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0235
  article-title: Machine learning and data mining in manufacturing
  publication-title: Expert Systems with Applications
  doi: 10.1016/j.eswa.2020.114060
– volume: 9
  start-page: 46022
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0750
  article-title: Design of active fault tolerant control system for air fuel ratio control of internal combustion engines using artificial neural networks
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2021.3068164
– volume: 12
  start-page: 2941
  issue: 12
  year: 2000
  ident: 10.1016/j.eswa.2023.121956_b0130
  article-title: A quantitative study of fault tolerance, noise immunity, and generalization ability of MLPs
  publication-title: Neural Computation
  doi: 10.1162/089976600300014782
– ident: 10.1016/j.eswa.2023.121956_b1050
  doi: 10.23919/WAC.2018.8430387
– volume: 26
  start-page: 83
  issue: 1
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0730
  article-title: Analysis of L2 regularization hyper parameter for stock price prediction
  publication-title: Journal of Institute of Science and Technology
  doi: 10.3126/jist.v26i1.37830
– volume: 67
  start-page: 2326
  issue: 3
  year: 2020
  ident: 10.1016/j.eswa.2023.121956_b0950
  article-title: An incorrect data detection method for big data cleaning of machinery condition monitoring
  publication-title: IEEE Transactions on Industrial Electronics
  doi: 10.1109/TIE.2019.2903774
– ident: 10.1016/j.eswa.2023.121956_b0155
– volume: 130
  start-page: 377
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0570
  article-title: Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification
  publication-title: Signal Processing
  doi: 10.1016/j.sigpro.2016.07.028
– volume: 63
  start-page: 2651
  issue: 11
  year: 2014
  ident: 10.1016/j.eswa.2023.121956_b0510
  article-title: Fault detection and classification in medium voltage DC shipboard power systems with wavelets and artificial neural networks
  publication-title: IEEE Transactions on Instrumentation and Measurement
  doi: 10.1109/TIM.2014.2313035
– volume: 20
  start-page: 1691
  issue: 2
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0140
  article-title: A novel approach for marine diesel engine fault diagnosis
  publication-title: Cluster Computing
  doi: 10.1007/s10586-017-0748-0
– start-page: 1
  year: 2015
  ident: 10.1016/j.eswa.2023.121956_b0270
– volume: 127
  start-page: 190
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0590
  article-title: Deep residual learning with demodulated time-frequency features for fault diagnosis of planetary gearbox under nonstationary running conditions
  publication-title: Mechanical Systems and Signal Processing
  doi: 10.1016/j.ymssp.2019.02.055
– ident: 10.1016/j.eswa.2023.121956_b0695
  doi: 10.1155/2019/8716979
– volume: 12
  start-page: 1
  issue: 1
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0470
  article-title: Reliability analysis of safety-critical and control systems: A state-of-the-art review
  publication-title: IET Software
  doi: 10.1049/iet-sen.2017.0053
– volume: 15
  start-page: 5139
  issue: 9
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0870
  article-title: A hierarchical deep domain adaptation approach for fault diagnosis of power plant thermal system
  publication-title: IEEE Transactions on Industrial Informatics
  doi: 10.1109/TII.2019.2899118
– ident: 10.1016/j.eswa.2023.121956_b0815
– start-page: 2397
  year: 2005
  ident: 10.1016/j.eswa.2023.121956_b0495
  article-title: Reliability modeling of fault tolerant control systems
– ident: 10.1016/j.eswa.2023.121956_b0485
– volume: 66
  start-page: 7316
  issue: 9
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0315
  article-title: Deep convolutional transfer learning network: A new method for intelligent fault diagnosis of machines with unlabeled data
  publication-title: IEEE Transactions on Industrial Electronics
  doi: 10.1109/TIE.2018.2877090
– volume: 118
  start-page: 159
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0850
  article-title: A bayesian inference-based approach for performance prognostics towards uncertainty quantification and its applications on the marine diesel engine
  publication-title: ISA Transactions
  doi: 10.1016/j.isatra.2021.02.024
– volume: 161
  start-page: 168
  year: 2015
  ident: 10.1016/j.eswa.2023.121956_b0700
  article-title: Scalable extensions of the ReliefF algorithm for weighting and selecting features on the multi-label learning context
  publication-title: Neurocomputing
  doi: 10.1016/j.neucom.2015.02.045
– volume: 8
  start-page: 1621
  issue: 9
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0415
  article-title: A fusion feature extraction method using EEMD and correlation coefficient analysis for bearing fault diagnosis
  publication-title: Applied Sciences
  doi: 10.3390/app8091621
– volume: 66
  start-page: 1926
  issue: 8
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0230
  article-title: Energy-Fluctuated multiscale feature learning with deep ConvNet for intelligent spindle bearing fault diagnosis
  publication-title: IEEE Transactions on Instrumentation and Measurement
  doi: 10.1109/TIM.2017.2674738
– volume: 7
  start-page: 515
  issue: 5
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0685
  article-title: Detection of pitting in gears using a deep sparse autoencoder
  publication-title: Applied Sciences
  doi: 10.3390/app7050515
– ident: 10.1016/j.eswa.2023.121956_b0740
  doi: 10.1561/9781680836394
– volume: 66
  start-page: 4696
  issue: 6
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b1075
  article-title: Multiple wavelet coefficients fusion in deep residual networks for fault diagnosis
  publication-title: IEEE Transactions on Industrial Electronics
  doi: 10.1109/TIE.2018.2866050
– volume: 160
  start-page: 237
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0435
  article-title: A multivariate encoder information based convolutional neural network for intelligent fault diagnosis of planetary gearboxes
  publication-title: Knowledge-Based Systems
  doi: 10.1016/j.knosys.2018.07.017
– start-page: 179
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0960
  article-title: Machine learning in expert systems for disease diagnostics in human healthcare
– ident: 10.1016/j.eswa.2023.121956_b0220
– volume: 32
  start-page: 37
  issue: 1
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b1010
  article-title: Fault diagnosis of planetary gearbox with incomplete information using assignment reduction and flexible naive bayesian classifier
  publication-title: Journal of Mechanical Science and Technology
  doi: 10.1007/s12206-017-1205-y
– ident: 10.1016/j.eswa.2023.121956_b0030
  doi: 10.1109/eSmarTA56775.2022.9935414
– ident: 10.1016/j.eswa.2023.121956_b0215
  doi: 10.1155/2017/5067651
– volume: 32
  start-page: 75
  issue: 1
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0205
  article-title: Signal-Based intelligent hydraulic fault diagnosis methods: Review and prospects
  publication-title: Chinese Journal of Mechanical Engineering
  doi: 10.1186/s10033-019-0388-9
– volume: 6
  start-page: 26241
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0145
  article-title: Preprocessing-Free gear fault diagnosis using small datasets with deep convolutional neural Network-Based transfer learning
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2018.2837621
– volume: 66
  start-page: 3196
  issue: 4
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0420
  article-title: Multiscale convolutional neural networks for fault diagnosis of wind turbine gearbox
  publication-title: IEEE Transactions on Industrial Electronics
  doi: 10.1109/TIE.2018.2844805
– volume: 69
  start-page: 9485
  issue: 12
  year: 2020
  ident: 10.1016/j.eswa.2023.121956_b0865
  article-title: Active fault tolerant control for unmanned underwater vehicle with sensor faults
  publication-title: IEEE Transactions on Instrumentation and Measurement
  doi: 10.1109/TIM.2020.3003108
– volume: 52
  start-page: 473
  issue: 5–6
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0070
  article-title: Hybrid fault tolerant control for air–fuel ratio control of internal combustion gasoline engine using kalman filters with advanced redundancy
  publication-title: Measurement and Control
  doi: 10.1177/0020294019842593
– ident: 10.1016/j.eswa.2023.121956_b0240
  doi: 10.1177/0959651819866281
– volume: 8
  start-page: 2885
  year: 2020
  ident: 10.1016/j.eswa.2023.121956_b0840
  article-title: A novel resilient robot: Kinematic analysis and experimentation
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2019.2962058
– volume: 4
  start-page: 217
  issue: 3
  year: 2013
  ident: 10.1016/j.eswa.2023.121956_b0120
  article-title: Parameter selection algorithm with self adaptive growing neural network classifier for diagnosis issues
  publication-title: International Journal of Machine Learning and Cybernetics
  doi: 10.1007/s13042-012-0089-5
– start-page: 770
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b0360
– volume: 578
  start-page: 887
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0795
  article-title: Feature selection using fisher score and multilabel neighborhood rough sets for multilabel classification
  publication-title: Information Sciences
  doi: 10.1016/j.ins.2021.08.032
– volume: 22
  start-page: 6448
  issue: 17
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0010
  article-title: A centrifugal pump fault diagnosis framework based on supervised contrastive learning
  publication-title: Sensors
  doi: 10.3390/s22176448
– volume: 14
  start-page: 1137
  issue: 3
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0585
  article-title: Deep coupling autoencoder for fault diagnosis with multimodal sensory data
  publication-title: IEEE Transactions on Industrial Informatics
  doi: 10.1109/TII.2018.2793246
– volume: 12
  start-page: 7841
  issue: 15
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0040
  article-title: A comparative study of design of active Fault-Tolerant control system for Air-Fuel ratio control of internal combustion engine using particle swarm optimization, genetic algorithm, and nonlinear Regression-Based observer model
  publication-title: Applied Sciences
  doi: 10.3390/app12157841
– volume: 66
  start-page: 3249
  issue: 12
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0615
  article-title: Low complexity motor current signature analysis using Sub-Nyquist strategy with reduced data length
  publication-title: IEEE Transactions on Instrumentation and Measurement
  doi: 10.1109/TIM.2017.2737879
– volume: 2
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0675
  article-title: A review of feature selection methods for machine Learning-Based disease risk prediction
  publication-title: Frontiers in Bioinformatics
  doi: 10.3389/fbinf.2022.927312
– volume: 108
  start-page: 262
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0655
  article-title: Gear fault diagnosis using transmission error and ensemble empirical mode decomposition
  publication-title: Mechanical Systems and Signal Processing
  doi: 10.1016/j.ymssp.2018.02.028
– volume: 6
  start-page: 339
  issue: 3
  year: 2008
  ident: 10.1016/j.eswa.2023.121956_b0880
  article-title: Active Fault-Tolerant control for a class of nonlinear systems with sensor faults
  publication-title: International Journal of control, Automation, and systems
– volume: 62
  start-page: 1
  year: 2014
  ident: 10.1016/j.eswa.2023.121956_b0805
  article-title: Fault diagnosis for a wind turbine transmission system based on manifold learning and shannon wavelet support vector machine
  publication-title: Renewable Energy
  doi: 10.1016/j.renene.2013.06.025
– volume: 27
  start-page: 2140
  issue: 11
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0705
  article-title: Intuitionistic fuzzy twin support vector machines
  publication-title: IEEE Transactions on fuzzy Systems
  doi: 10.1109/TFUZZ.2019.2893863
– volume: 106
  start-page: 142
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0395
  article-title: Automated bearing fault diagnosis scheme using 2D representation of wavelet packet transform and deep convolutional neural network
  publication-title: Computers in Industry
  doi: 10.1016/j.compind.2019.01.008
– volume: 428
  start-page: 72
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0535
  article-title: Early fault diagnosis of rolling bearings based on hierarchical symbol dynamic entropy and binary tree support vector machine
  publication-title: Journal of Sound and Vibration
  doi: 10.1016/j.jsv.2018.04.036
– volume: 22
  start-page: 1345
  issue: 10
  year: 2010
  ident: 10.1016/j.eswa.2023.121956_b0640
  article-title: A survey on transfer learning
  publication-title: IEEE Transactions on Knowledge and Data Engineering
  doi: 10.1109/TKDE.2009.191
– volume: 7
  start-page: 17634
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0065
  article-title: Advanced fault tolerant Air-Fuel ratio control of internal combustion gas engine for sensor and actuator faults
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2019.2894796
– volume: 35
  start-page: 242
  issue: 9
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0440
  article-title: An effective crack position diagnosis method for the hollow shaft rotor system based on the convolutional neural network and deep metric learning
  publication-title: Chinese Journal of Aeronautics
  doi: 10.1016/j.cja.2021.09.010
– volume: 34
  start-page: 3451
  issue: 6
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0670
  article-title: Feature engineering based on ANOVA, cluster validity assessment and KNN for fault diagnosis in bearings
  publication-title: Journal of Intelligent & Fuzzy Systems
– volume: 4
  start-page: 99
  issue: 2
  year: 2010
  ident: 10.1016/j.eswa.2023.121956_b1040
  article-title: On the principle of design of resilient systems – application to enterprise information systems
  publication-title: Enterprise Information Systems
  doi: 10.1080/17517571003763380
– ident: 10.1016/j.eswa.2023.121956_b0325
– volume: 15
  start-page: 2446
  issue: 4
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0770
  article-title: Highly accurate machine fault diagnosis using deep transfer learning
  publication-title: IEEE Transactions on Industrial Informatics
  doi: 10.1109/TII.2018.2864759
– volume: 9
  start-page: 9429
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0785
  article-title: ANN assisted multi sensor information fusion for BLDC motor fault diagnosis
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2021.3050243
– ident: 10.1016/j.eswa.2023.121956_b0560
– volume: 1–16
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0080
  article-title: Robust passive fault tolerant control for air fuel ratio control of internal combustion gasoline engine for sensor and actuator faults
  publication-title: IETE Journal of Research
– ident: 10.1016/j.eswa.2023.121956_b0595
– volume: 107
  start-page: 241
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0450
  article-title: A review on the application of deep learning in system health management
  publication-title: Mechanical Systems and Signal Processing
  doi: 10.1016/j.ymssp.2017.11.024
– volume: 229
  start-page: 304
  issue: 2
  year: 2015
  ident: 10.1016/j.eswa.2023.121956_b0545
  article-title: Condition monitoring and fault diagnosis of diesel engines using instantaneous angular speed analysis
  publication-title: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
– volume: 48
  start-page: 34
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b1065
  article-title: Imbalanced data fault diagnosis of rotating machinery using synthetic oversampling and feature learning
  publication-title: Journal of Manufacturing Systems
  doi: 10.1016/j.jmsy.2018.04.005
– volume: 38
  start-page: 2255
  issue: 8
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b0250
  article-title: Application of fuzzy c-means method and classification model of optimized k-nearest neighbor for fault diagnosis of bearing
  publication-title: Journal of the Brazilian Society of Mechanical Sciences and Engineering
  doi: 10.1007/s40430-015-0455-9
– volume: 170
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0625
  article-title: New bearing slight degradation detection approach based on the periodicity intensity factor and signal processing methods
  publication-title: Measurement
  doi: 10.1016/j.measurement.2020.108696
– volume: Vol. 52
  start-page: 1879
  year: 2023
  ident: 10.1016/j.eswa.2023.121956_b0610
  article-title: Artificial neural networks-based identification of the WWTP DO sensor types of faults
– start-page: 2200
  year: 2013
  ident: 10.1016/j.eswa.2023.121956_b0555
  article-title: Transfer feature learning with joint distribution adaptation
– volume: 255
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0480
  article-title: Takagi-Sugeno fuzzy based power system fault section diagnosis models via genetic learning adaptive GSK algorithm
  publication-title: Knowledge-Based Systems
  doi: 10.1016/j.knosys.2022.109773
– volume: 33
  start-page: 505
  issue: 2
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0305
  article-title: Fault diagnosis of rolling element bearing based on artificial neural network
  publication-title: Journal of Mechanical Science and Technology
  doi: 10.1007/s12206-019-0103-x
– volume: 65
  start-page: 11
  issue: 3
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b0985
  article-title: Feature knowledge based fault detection of induction motors through the analysis of stator current data
  publication-title: IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
  doi: 10.1109/TIM.2015.2498978
– volume: 96
  start-page: 803
  issue: 1–4
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0260
  article-title: Development and trend of condition monitoring and fault diagnosis of multi-sensors information fusion for rolling bearings: A review
  publication-title: The International Journal of Advanced Manufacturing Technology
  doi: 10.1007/s00170-017-1474-8
– volume: 30
  start-page: 1197
  issue: 5
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0800
  article-title: Feature selection with missing labels using multilabel fuzzy neighborhood rough sets and maximum relevance minimum redundancy
  publication-title: IEEE Transactions on fuzzy Systems
  doi: 10.1109/TFUZZ.2021.3053844
– year: 2016
  ident: 10.1016/j.eswa.2023.121956_b0295
– volume: 95
  start-page: 187
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0765
  article-title: A novel deep autoencoder feature learning method for rotating machinery fault diagnosis
  publication-title: Mechanical Systems and Signal Processing
  doi: 10.1016/j.ymssp.2017.03.034
– volume: 2018
  start-page: 1309
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0935
  article-title: A transfer learning strategy for rotation machinery fault diagnosis based on Cycle-Consistent generative adversarial networks
  publication-title: Chinese Automation Congress (CAC)
– volume: 127
  start-page: 246
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0350
  article-title: Multi-level wavelet packet fusion in dynamic ensemble convolutional neural network for fault diagnosis
  publication-title: Measurement
  doi: 10.1016/j.measurement.2018.05.098
– volume: 272
  start-page: 619
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0405
  article-title: A neural network constructed by deep learning technique and its application to intelligent fault diagnosis of machines
  publication-title: Neurocomputing
  doi: 10.1016/j.neucom.2017.07.032
– volume: 66–67
  start-page: 679
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b0875
  article-title: Spectral kurtosis for fault detection, diagnosis and prognostics of rotating machines: A review with applications
  publication-title: Mechanical Systems and Signal Processing
  doi: 10.1016/j.ymssp.2015.04.039
– volume: 32
  start-page: 5201
  issue: 11
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b1015
  article-title: Rolling bearing fault diagnosis based on mean multigranulation decision-theoretic rough set and non-naive bayesian classifier
  publication-title: Journal of Mechanical Science and Technology
  doi: 10.1007/s12206-018-1018-7
– volume: 8
  start-page: 2357
  issue: 12
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0355
  article-title: Bearing fault diagnosis under variable rotational speeds using stockwell Transform-Based vibration imaging and transfer learning
  publication-title: Applied Sciences
  doi: 10.3390/app8122357
– volume: 25
  start-page: 1880
  issue: 12
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b1005
  article-title: Multiscale representations fusion with joint multiple reconstructions autoencoder for intelligent fault diagnosis
  publication-title: IEEE Signal Processing Letters
  doi: 10.1109/LSP.2018.2878356
– volume: 79
  start-page: 65
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0225
  article-title: Stability-based system for bearing fault early detection
  publication-title: Expert Systems with Applications
  doi: 10.1016/j.eswa.2017.02.030
– volume: 259
  start-page: 252
  year: 2014
  ident: 10.1016/j.eswa.2023.121956_b0365
  article-title: Bayesian classifiers based on probability density estimation and their applications to simultaneous fault diagnosis
  publication-title: Information Sciences
  doi: 10.1016/j.ins.2013.09.003
– volume: 65
  start-page: 4290
  issue: 5
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b1070
  article-title: Deep residual networks with dynamically weighted wavelet coefficients for fault diagnosis of planetary gearboxes
  publication-title: IEEE Transactions on Industrial Electronics
  doi: 10.1109/TIE.2017.2762639
– volume: 39
  start-page: 1000
  issue: 7
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0095
  article-title: Application of variational mode decomposition energy distribution to bearing fault diagnosis in a wind turbine
  publication-title: Transactions of the Institute of Measurement and Control
  doi: 10.1177/0142331215626247
– volume: 117
  year: 2023
  ident: 10.1016/j.eswa.2023.121956_b0160
  article-title: Multiple fault detection and isolation using artificial neural networks in sensors of an internal combustion engine
  publication-title: Engineering Applications of Artificial Intelligence
  doi: 10.1016/j.engappai.2022.105524
– volume: 122
  start-page: 502
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0680
  article-title: Applications of stochastic resonance to machinery fault detection: A review and tutorial
  publication-title: Mechanical Systems and Signal Processing
  doi: 10.1016/j.ymssp.2018.12.032
– volume: 91
  start-page: 295
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0530
  article-title: A fault diagnosis scheme for planetary gearboxes using modified multi-scale symbolic dynamic entropy and mRMR feature selection
  publication-title: Mechanical Systems and Signal Processing
  doi: 10.1016/j.ymssp.2016.12.040
– volume: 51
  start-page: 470
  issue: 18
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0375
  article-title: Fault detection and classification using artificial neural networks
  publication-title: IFAC-PapersOnLine
  doi: 10.1016/j.ifacol.2018.09.380
– volume: 17
  start-page: 1729
  issue: 8
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0505
  article-title: An ensemble deep convolutional neural network model with improved d-S evidence fusion for bearing fault diagnosis
  publication-title: Sensors
  doi: 10.3390/s17081729
– volume: 77
  start-page: 354
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0300
  article-title: Recent advances in convolutional neural networks
  publication-title: Pattern Recognition
  doi: 10.1016/j.patcog.2017.10.013
– volume: 230
  start-page: 291
  issue: 2
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b0825
  article-title: Two-stage feature selection for bearing fault diagnosis based on dual-tree complex wavelet transform and empirical mode decomposition
  publication-title: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
– volume: 68
  start-page: 6248
  issue: 7
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0780
  article-title: Fault diagnosis of an autonomous vehicle with an improved SVM algorithm subject to unbalanced datasets
  publication-title: IEEE Transactions on Industrial Electronics
  doi: 10.1109/TIE.2020.2994868
– volume: 18
  start-page: 4460
  issue: 12
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0410
  article-title: Symbolic important point perceptually and hidden markov model based hydraulic pump fault diagnosis method
  publication-title: Sensors
  doi: 10.3390/s18124460
– volume: 66
  start-page: 5525
  issue: 7
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0515
  article-title: Cross-Domain fault diagnosis of rolling element bearings using deep generative neural networks
  publication-title: IEEE Transactions on Industrial Electronics
  doi: 10.1109/TIE.2018.2868023
– ident: 10.1016/j.eswa.2023.121956_b0915
– volume: 51
  start-page: 4091
  issue: 7
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b1035
  article-title: Neural Networks-Based fault tolerant control of a robot via fast terminal sliding mode
  publication-title: IEEE Transactions on Systems, Man, and Cybernetics: Systems
  doi: 10.1109/TSMC.2019.2933050
– volume: 10
  start-page: 245
  issue: 3
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b1045
  article-title: Design theory and methodology for enterprise systems
  publication-title: Enterprise Information Systems
  doi: 10.1080/17517575.2015.1080860
– volume: 37
  start-page: 276
  issue: 1–2
  year: 2013
  ident: 10.1016/j.eswa.2023.121956_b0115
  article-title: Hard competitive growing neural network for the diagnosis of small bearing faults
  publication-title: Mechanical Systems and Signal Processing
  doi: 10.1016/j.ymssp.2012.11.002
– volume: 108
  start-page: 134
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0135
  article-title: Bearing faults diagnosis using fuzzy expert system relying on an improved range overlaps and similarity method
  publication-title: Expert Systems with Applications
  doi: 10.1016/j.eswa.2018.04.025
– volume: 9
  start-page: 152616
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0460
  article-title: KNN-SC: Novel spectral clustering algorithm using k-Nearest neighbors
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2021.3126854
– volume: 28
  start-page: 04014065
  issue: 2
  year: 2015
  ident: 10.1016/j.eswa.2023.121956_b0885
  article-title: Fault early recognition and health monitoring on aeroengine rotor system
  publication-title: Journal of Aerospace Engineering
  doi: 10.1061/(ASCE)AS.1943-5525.0000386
– volume: 5
  start-page: 6027
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0995
  article-title: Rolling element bearing fault diagnosis using improved manifold learning
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2017.2693379
– volume: 60
  start-page: 84
  issue: 6
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0465
  article-title: ImageNet classification with deep convolutional neural networks
  publication-title: Communications of the ACM
  doi: 10.1145/3065386
– volume: 21
  start-page: 1727
  issue: 2
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0195
  article-title: Infrared Thermography-Based fault diagnosis of induction motor bearings using machine learning
  publication-title: IEEE Sensors Journal
  doi: 10.1109/JSEN.2020.3015868
– volume: 15
  start-page: 5666
  issue: 15
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0050
  article-title: Design of a hybrid Fault-Tolerant control system for Air-Fuel ratio control of internal combustion engines using genetic algorithm and Higher-Order sliding mode control
  publication-title: Energies
  doi: 10.3390/en15155666
– volume: 49
  start-page: 136
  issue: 1
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0910
  article-title: A new deep transfer learning based on sparse Auto-Encoder for fault diagnosis
  publication-title: IEEE Transactions on Systems, Man, and Cybernetics: Systems
  doi: 10.1109/TSMC.2017.2754287
– volume: 43
  start-page: 18
  issue: 1
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0940
  article-title: Prediction of hemodialysis timing based on LVW feature selection and ensemble learning
  publication-title: Journal of Medical Systems
  doi: 10.1007/s10916-018-1136-x
– volume: 51
  start-page: 309
  issue: 18
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0945
  article-title: A platform for fault diagnosis of High-Speed train based on big data
  publication-title: IFAC-PapersOnLine
  doi: 10.1016/j.ifacol.2018.09.318
– volume: 17
  start-page: 1947
  issue: 3
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0085
  article-title: Unified Fault-Tolerant control for Air-Fuel ratio control of internal combustion engines with advanced analytical and hardware redundancies
  publication-title: Journal of Electrical Engineering & Technology
  doi: 10.1007/s42835-021-00965-5
– volume: 2016
  start-page: 1
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b0930
  article-title: on cross-domain feature fusion in gearbox fault diagnosis under various operating conditions based on transfer component analysis
  publication-title: IEEE International Conference on Prognostics and Health Management (ICPHM)
– volume: 7
  start-page: 2530
  issue: 4
  year: 2021
  ident: 10.1016/j.eswa.2023.121956_b0150
  article-title: Fault-Tolerant controller design for path following of the autonomous vehicle under the faults in braking actuators
  publication-title: IEEE Transactions on Transportation Electrification
  doi: 10.1109/TTE.2021.3071725
– volume: 9
  start-page: 379
  issue: 6
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b0990
  article-title: Representational learning for fault diagnosis of wind turbine equipment: A Multi-Layered extreme learning machines approach
  publication-title: Energies
  doi: 10.3390/en9060379
– volume: 198
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0185
  article-title: Deep residual network based fault detection and diagnosis of photovoltaic arrays using current-voltage curves and ambient conditions
  publication-title: Energy Conversion and Management
  doi: 10.1016/j.enconman.2019.111793
– volume: 8
  start-page: 1859
  issue: 10
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0810
  article-title: Fault diagnosis of rolling bearings based on improved fast spectral correlation and optimized random forest
  publication-title: Applied Sciences
  doi: 10.3390/app8101859
– ident: 10.1016/j.eswa.2023.121956_b0725
  doi: 10.1784/insi.2017.59.12.669
– ident: 10.1016/j.eswa.2023.121956_b0210
  doi: 10.1145/1273496.1273521
– volume: 85
  start-page: 56
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0105
  article-title: Diagnosis of combined faults in rotary machinery by Non-Naive bayesian approach
  publication-title: Mechanical Systems and Signal Processing
  doi: 10.1016/j.ymssp.2016.08.005
– start-page: 19
  year: 2013
  ident: 10.1016/j.eswa.2023.121956_b0265
  article-title: Dependability evaluation techniques
– volume: 131
  start-page: 524
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b0790
  article-title: Faulty bearing detection, classification and location in a three-phase induction motor based on stockwell transform and support vector machine
  publication-title: Measurement
  doi: 10.1016/j.measurement.2018.09.013
– volume: 7
  start-page: 41
  issue: 1
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0320
  article-title: Deep fault recognizer: an integrated model to denoise and extract features for fault diagnosis in rotating machinery
  publication-title: Applied Sciences
  doi: 10.3390/app7010041
– volume: 9
  issue: 12
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0335
  article-title: A new fault diagnosis method based on deep belief network and support vector machine with Teager-Kaiser energy operator for bearings
  publication-title: Advances in Mechanical Engineering
  doi: 10.1177/1687814017743113
– ident: 10.1016/j.eswa.2023.121956_b0175
– volume: 53
  start-page: 3550
  issue: 7
  year: 2015
  ident: 10.1016/j.eswa.2023.121956_b0600
  article-title: Semisupervised transfer component analysis for domain adaptation in remote sensing image classification
  publication-title: IEEE Transactions on Geoscience and remote sensing
  doi: 10.1109/TGRS.2014.2377785
– volume: 117
  start-page: 20
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0290
  article-title: Diagnosis of stator faults of the single-phase induction motor using acoustic signals
  publication-title: Applied Acoustics
  doi: 10.1016/j.apacoust.2016.10.012
– volume: 63
  start-page: 7067
  issue: 11
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b0385
  article-title: Real-Time motor fault detection by 1-D convolutional neural networks
  publication-title: IEEE Transactions on Industrial Electronics
  doi: 10.1109/TIE.2016.2582729
– volume: 41
  start-page: 113
  issue: 1–2
  year: 2013
  ident: 10.1016/j.eswa.2023.121956_b0430
  article-title: Feature extraction based on semi-supervised kernel marginal fisher analysis and its application in bearing fault diagnosis
  publication-title: Mechanical Systems and Signal Processing
  doi: 10.1016/j.ymssp.2013.05.017
– volume: 64
  start-page: 2296
  issue: 3
  year: 2017
  ident: 10.1016/j.eswa.2023.121956_b0575
  article-title: Deep model based domain adaptation for fault diagnosis
  publication-title: IEEE Transactions on Industrial Electronics
  doi: 10.1109/TIE.2016.2627020
– volume: 9
  start-page: 494
  issue: 2
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0400
  article-title: fault diagnosis of automobile systems using fault tree based on digraph modeling
  publication-title: International Journal of System Assurance Engineering and Management
– volume: 115
  start-page: 213
  year: 2019
  ident: 10.1016/j.eswa.2023.121956_b1080
  article-title: Deep learning and its applications to machine health monitoring
  publication-title: Mechanical Systems and Signal Processing
  doi: 10.1016/j.ymssp.2018.05.050
– volume: 3
  start-page: 9
  issue: 1
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b0905
  article-title: A survey of transfer learning
  publication-title: Journal of Big Data
  doi: 10.1186/s40537-016-0043-6
– ident: 10.1016/j.eswa.2023.121956_b0830
  doi: 10.1177/1475921717727700
– ident: 10.1016/j.eswa.2023.121956_b0775
  doi: 10.21595/jve.2017.18380
– volume: 9
  start-page: 539
  issue: 6
  year: 1998
  ident: 10.1016/j.eswa.2023.121956_b0275
  article-title: An expert system for engine fault diagnosis: Development and application
  publication-title: Journal of Intelligent Manufacturing
  doi: 10.1023/A:1008888219539
– volume: 144
  start-page: 65
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0855
  article-title: Convolutional neural network-based hidden markov models for rolling element bearing fault identification
  publication-title: Knowledge-Based Systems
  doi: 10.1016/j.knosys.2017.12.027
– volume: 55
  start-page: 724
  issue: 6
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0900
  article-title: Fault-Tolerant control for a high altitude long endurance aircraft
  publication-title: IFAC-PapersOnLine
  doi: 10.1016/j.ifacol.2022.07.213
– start-page: 1
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b0005
  article-title: Reliability enhancement of modular multilevel converter by applying fault tolerant control
– ident: 10.1016/j.eswa.2023.121956_b0280
  doi: 10.17531/ein.2017.1.5
– volume: 200
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0330
  article-title: Ensemble feature selection using distance-based supervised and unsupervised methods in binary classification
  publication-title: Expert Systems with Applications
  doi: 10.1016/j.eswa.2022.116794
– volume: 12
  start-page: 297
  issue: 3
  year: 2015
  ident: 10.1016/j.eswa.2023.121956_b0380
  article-title: Reliability optimization of automatic control systems based on importance measures: A framework
  publication-title: International Journal of Performability Engineering
– volume: 230
  start-page: 303
  issue: 2
  year: 2016
  ident: 10.1016/j.eswa.2023.121956_b1020
  article-title: Combined flow graphs and normal naive bayesian classifier for fault diagnosis of gear box
  publication-title: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
– volume: 319
  start-page: 155
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0310
  article-title: A hybrid feature model and deep learning based fault diagnosis for unmanned aerial vehicle sensors
  publication-title: Neurocomputing
  doi: 10.1016/j.neucom.2018.08.046
– volume: 230
  start-page: 542
  year: 2014
  ident: 10.1016/j.eswa.2023.121956_b0180
  article-title: Fault diagnosis based on comprehensive geometric characteristic and probability neural network
  publication-title: Applied Mathematics and Computation
  doi: 10.1016/j.amc.2013.12.122
– volume: 6
  start-page: 63584
  year: 2018
  ident: 10.1016/j.eswa.2023.121956_b0925
  article-title: An End-to-End model based on improved adaptive deep belief network and its application to bearing fault diagnosis
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2018.2877447
– volume: 160
  year: 2022
  ident: 10.1016/j.eswa.2023.121956_b0015
  article-title: Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the context of smart grid paradigm
  publication-title: Renewable and Sustainable Energy Reviews
  doi: 10.1016/j.rser.2022.112128
SSID ssj0017007
Score 2.6132708
SecondaryResourceType review_article
Snippet Intelligent Fault-Tolerant Control (IFTC) refers to the applications of machine learning algorithms for fault diagnosis and design of Fault-Tolerant Control...
SourceID crossref
elsevier
SourceType Enrichment Source
Index Database
Publisher
StartPage 121956
SubjectTerms Algorithms
Deep learning
Fault diagnosis
Intelligent fault-tolerant control
Machine learning
Transfer learning
Title Development of Intelligent Fault-Tolerant Control Systems with Machine Learning, Deep Learning, and Transfer Learning Algorithms: A Review
URI https://dx.doi.org/10.1016/j.eswa.2023.121956
Volume 238
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVESC
  databaseName: Baden-Württemberg Complete Freedom Collection (Elsevier)
  customDbUrl:
  eissn: 1873-6793
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0017007
  issn: 0957-4174
  databaseCode: GBLVA
  dateStart: 20110101
  isFulltext: true
  titleUrlDefault: https://www.sciencedirect.com
  providerName: Elsevier
– providerCode: PRVESC
  databaseName: Elsevier SD Complete Freedom Collection [SCCMFC]
  customDbUrl:
  eissn: 1873-6793
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0017007
  issn: 0957-4174
  databaseCode: ACRLP
  dateStart: 19950101
  isFulltext: true
  titleUrlDefault: https://www.sciencedirect.com
  providerName: Elsevier
– providerCode: PRVESC
  databaseName: Elsevier SD Freedom Collection Journals [SCFCJ]
  customDbUrl:
  eissn: 1873-6793
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0017007
  issn: 0957-4174
  databaseCode: AIKHN
  dateStart: 19950101
  isFulltext: true
  titleUrlDefault: https://www.sciencedirect.com
  providerName: Elsevier
– providerCode: PRVESC
  databaseName: Science Direct
  customDbUrl:
  eissn: 1873-6793
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0017007
  issn: 0957-4174
  databaseCode: .~1
  dateStart: 19950101
  isFulltext: true
  titleUrlDefault: https://www.sciencedirect.com
  providerName: Elsevier
– providerCode: PRVLSH
  databaseName: Elsevier Journals
  customDbUrl:
  mediaType: online
  eissn: 1873-6793
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0017007
  issn: 0957-4174
  databaseCode: AKRWK
  dateStart: 19900101
  isFulltext: true
  providerName: Library Specific Holdings
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV09T8MwELUqWFj4RnxWHtjAtEntJGWLClULKgtU6hY59bkqKm0Fqdj4Afxq7hKnKhLqwGjLp0Q-5945fn7H2GVgZKhTaYQBawXplwjdlFKg-4OmZxHwU7oo3HsKOn35MFCDCmuVd2GIVulifxHT82jtempuNmvz8bj2jMkBwiGdNNLxYURxWMqQqhjcfC1pHiQ_FxZ6e6Gg0e7iTMHxgo9P0h7yGySy0KQi1n-B0wrgtHfZtssUeVy8zB6rwHSf7ZRVGLj7KA_Y9wrvh88s7y5FNjPe1otJJl5mE0BIynir4KVzJ1PO6Scs7-V0SuBOaXV0ze8A5itNPTU8hzSLjy27eTwZzd7R_u3jlse8OGI4ZP32_UurI1yFBTFs1OuZGFrbgEhjEqBw20TiV9JGQ2W91GAiZ3Q91FHoQwhNPwBrpKcjE2jr-RCkOOemccQ2prMpHDOOKCeVryHUykoFON8Gd0KpgsD61k_rJ8wrpzYZOvlxqoIxSUqe2WtC7kjIHUnhjhN2tbSZF-Iba0er0mPJryWUIDqssTv9p90Z28KWJEKap87ZRva-gAvMULK0mi_BKtuMu4-dpx-ybuZd
linkProvider Elsevier
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LTwIxEG6IHvTi2_i2B29aYZd2d_FGUIIPuAgJt02XTokGgcASb_4Af7UzbJdgYjh43G4nu5npzjfdfv3K2FVgZKgTaYQBawXplwhdkVJg-IOKZxHwE9oo3GwFjY586qpugdXyvTBEq3S5P8vp82ztWorOm8Xx21vxFYsDhENaaaTlwwjz8LpUfkgzsNuvBc-D9OfCTHAvFNTd7ZzJSF4w_STxIb9MKgsVOsX6L3RaQpz6DttypSKvZm-zywow3GPb-TEM3H2V--x7ifjDR5Y_LlQ2U17Xs0Eq2qMBICalvJYR07nTKef0F5Y353xK4E5qtX_D7wHGS5d6aPgc0yw-Nm_m1UF_NEH7j-kdr_JsjeGAdeoP7VpDuCMWRK9cKqWiZ20ZIo1VgMJ5E6lfSRv1lPUSg5Wc0aVQR6EPIVT8AKyRno5MoK3nQ5Cg0035kK0NR0M4YhxhDt2vIdTKSgXob4NToURBYH3rJ6Vj5uWujXtOf5yOwRjEOdHsPaZwxBSOOAvHMbte2Iwz9Y2VvVUesfjXGIoRHlbYnfzT7pJtNNrNl_jlsfV8yjbxjiR2mqfO2Fo6mcE5litpcjEfjj8Y6efy
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Development+of+Intelligent+Fault-Tolerant+Control+Systems+with+Machine+Learning%2C+Deep+Learning%2C+and+Transfer+Learning+Algorithms%3A+A+Review&rft.jtitle=Expert+systems+with+applications&rft.au=Amin%2C+Arslan+Ahmed&rft.au=Sajid+Iqbal%2C+Muhammad&rft.au=Hamza+Shahbaz%2C+Muhammad&rft.date=2024-03-15&rft.issn=0957-4174&rft.volume=238&rft.spage=121956&rft_id=info:doi/10.1016%2Fj.eswa.2023.121956&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_eswa_2023_121956
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0957-4174&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0957-4174&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0957-4174&client=summon