Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems - Couverture rigide

Yang, Rui; Zhong, Maiying

Couverture rigide

ISBN 10 : 1032147253 ISBN 13 : 9781032147253

Editeur : CRC Press, 2022

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.

A propos du livre

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.

Détails de l'édition

• Éditeur: CRC Press
• Date d'édition: 2022
• Langue: anglais
• ISBN 10: 1032147253
• ISBN 13: 9781032147253
• Reliure: Relié
• Nombre de pages: 92
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible