Fuzzy-Based Intelligent Algorithm for Diagnosis of Drive Faults in Induction Motor Drive System
This paper presents the design and development of a novel, fuzzy-based algorithm for the detection and diagnosis of drive faults in an induction motor drive system (IMDS). A detailed investigation on the performance of IMDS under various faults and load conditions revealed that the combination of ro...
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| Published in | Arabian journal for science and engineering (2011) Vol. 45; no. 3; pp. 1385 - 1395 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.03.2020
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2193-567X 1319-8025 2191-4281 |
| DOI | 10.1007/s13369-019-03935-2 |
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| Abstract | This paper presents the design and development of a novel, fuzzy-based algorithm for the detection and diagnosis of drive faults in an induction motor drive system (IMDS). A detailed investigation on the performance of IMDS under various faults and load conditions revealed that the combination of root-mean-square value and total harmonic distortion (THD) of the stator currents can accurately transpire various fault conditions. In this work, the efficacy of fuzzy logic is employed to characterize and diagnose the fault since it is difficult to find crisp boundaries for the correlation between the extracted parameters and fault conditions. The performance of the developed algorithm is tested and verified using simulation in MATLAB Simulink. |
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| AbstractList | This paper presents the design and development of a novel, fuzzy-based algorithm for the detection and diagnosis of drive faults in an induction motor drive system (IMDS). A detailed investigation on the performance of IMDS under various faults and load conditions revealed that the combination of root-mean-square value and total harmonic distortion (THD) of the stator currents can accurately transpire various fault conditions. In this work, the efficacy of fuzzy logic is employed to characterize and diagnose the fault since it is difficult to find crisp boundaries for the correlation between the extracted parameters and fault conditions. The performance of the developed algorithm is tested and verified using simulation in MATLAB Simulink. |
| Author | Mini, V. P. Mayadevi, N. Prins, Shruti Hari Kumar, R. |
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| Keywords | Fuzzy logic Induction motor Motor drives Total harmonic distortion Fault detection |
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| SubjectTerms | Algorithms Computer simulation Conversion Engineering Fault detection Fault diagnosis Fuzzy logic Fuzzy systems Harmonic distortion Humanities and Social Sciences Induction motors multidisciplinary Research Article - Electrical Engineering Science |
| Title | Fuzzy-Based Intelligent Algorithm for Diagnosis of Drive Faults in Induction Motor Drive System |
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