Machine Learning-based Fault Diagnosis for Industrial Engineering Systems

Yang, Rui; Zhong, Maiying

ISBN 10: 1032147253 / ISBN 13: 9781032147253

Edité par CRC Press, 2022

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Unread book in perfect condition. N° de réf. du vendeur 44151573

Détails bibliographiques

Titre : Machine Learning-based Fault Diagnosis for ...

Éditeur : CRC Press

Date d'édition : 2022

Reliure : Couverture rigide

Etat : As New

A propos de ce titre

Synopsis :

This book provides advanced techniques for precision compensation and fault diagnosis of precision motion systems and rotating machinery. Techniques and applications through experiments and case studies for intelligent precision compensation and fault diagnosis are offered along with the introduction of machine learning and deep learning methods.

À propos de l?auteur:

Rui Yang received the B.Eng. degree in Computer Engineering and the Ph.D. degree in Electrical and Computer Engineering from National University of Singapore in 2008 and 2013 respectively. He is currently an Assistant Professor in the School of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou, China, and an Honorary Lecturer in the Department of Computer Science, University of Liverpool, Liverpool, United Kingdom. His research interests include machine learning based data analysis and applications.

Maiying Zhong received her Ph.D. degree in control theory and control engineering from the Northestern University, China, in 1999. From 2000 to 2001, she was a visiting Scholar at the University of Applied Sciences Lausitz, Germany. From 2002 to July 2008, she was a professor of the School of Control Science and Engineering at Shandong University. From 2006 to 2007, she was a Postdoctoral Researcher Fellow with the Central Queensland University, Australia. From 2009 to 2016, she was a professor of the School of Instrument Science and Opto-Electronics Engineering, Beihang University. In March 2016, she joined Shandong University of Science and Technology, China, where she is currently a professor with the College of Electrical Engineering and Automation. Her research interests are model based fault diagnosis, fault tolerant systems and their applications.