Data-driven fault detection for industrial processes : canonical correlation analysis and projection based methods

Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial processes. With the ever increasing demands on reliability and safety in industrial processes, fault detection has become an important issue. Although the model-based fault detection theory has been we...

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Bibliographic Details
Main Author: Chen, Zhiwen, (Author)
Format: eBook
Language: English
Published: Wiesbaden, Germany : Springer Vieweg, 2017.
Subjects:
Fault location (Engineering)
elektronické knihy
electronic books
ISBN: 9783658167561
9783658167554
Physical Description: 1 online resource

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100 1 |a Chen, Zhiwen,  |e author. 
245 1 0 |a Data-driven fault detection for industrial processes :  |b canonical correlation analysis and projection based methods /  |c Zhiwen Chen. 
264 1 |a Wiesbaden, Germany :  |b Springer Vieweg,  |c 2017. 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a počítač  |b c  |2 rdamedia 
338 |a online zdroj  |b cr  |2 rdacarrier 
504 |a Includes bibliographical references. 
505 0 |a A New Index for Performance Evaluation of FD Methods -- CCA-based FD Method for the Monitoring of Stationary Processes -- Projection-based FD Method for the Monitoring of Dynamic Processes -- Benchmark Study and Real-Time Implementation. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial processes. With the ever increasing demands on reliability and safety in industrial processes, fault detection has become an important issue. Although the model-based fault detection theory has been well studied in the past decades, its applications are limited to large-scale industrial processes because it is difficult to build accurate models. Furthermore, motivated by the limitations of existing data-driven FD methods, novel canonical correlation analysis (CCA) and projection-based methods are proposed from the perspectives of process input and output data, less engineering effort and wide application scope. For performance evaluation of FD methods, a new index is also developed. Contents A New Index for Performance Evaluation of FD Methods CCA-based FD Method for the Monitoring of Stationary Processes Projection-based FD Method for the Monitoring of Dynamic Processes Benchmark Study and Real-Time Implementation Target Groups Researchers and students in the field of process control and statistical hypothesis testing Research and development engineers in the process industry About the Author Zhiwen Chen?s research interests include multivariate statistical process monitoring, model-based and data-driven fault diagnosis as well as their application to industrial processes. He is currently working at the School of Information Science and Engineering at Central South University, China. 
590 |a SpringerLink  |b Springer Complete eBooks 
650 0 |a Fault location (Engineering) 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
776 0 8 |i Printed edition:  |z 9783658167554 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://link.springer.com/10.1007/978-3-658-16756-1  |y Plný text 
992 |c NTK-SpringerENG 
999 |c 99688  |d 99688 
993 |x NEPOSILAT  |y EIZ 

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