
Model-based Health Monitoring of Hybrid Systems
Springer (Publisher)
Published on 17. June 2015
Book
Paperback/Softback
XII, 297 pages
978-1-4899-9059-4 (ISBN)
Description
This book systematically presents a comprehensive framework and effective techniques for in-depth analysis, clear design procedure, and efficient implementation of diagnosis and prognosis algorithms for hybrid systems. It offers an overview of the fundamentals of diagnosis\prognosis and hybrid bond graph modeling. This book also describes hybrid bond graph-based quantitative fault detection, isolation and estimation. Moreover, it also presents strategies to track the system mode and predict the remaining useful life under multiple fault condition. A real world complex hybrid system-a vehicle steering control system-is studied using the developed fault diagnosis methods to show practical significance.
Readers of this book will benefit from easy-to-understand fundamentals of bond graph models, concepts of health monitoring, fault diagnosis and failure prognosis, as well as hybrid systems. The reader will gain knowledge of fault detection and isolation in complex systems including those with hybrid nature, and will learn state-of-the-art developments in theory and technologies of fault diagnosis and failure prognosis for complex systems.More details
Edition
2013
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Research
Illustrations
XII, 297 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 17 mm
Weight
476 gr
ISBN-13
978-1-4899-9059-4 (9781489990594)
DOI
10.1007/978-1-4614-7369-5
Schweitzer Classification
Other editions
Additional editions

Danwei Wang | Ming Yu | Chang Boon Low
Model-based Health Monitoring of Hybrid Systems
A Hybrid Bond Graph Approach
Book
05/2013
1st Edition
Springer
€106.99
Shipment within 15-20 days
Persons
Yuanzhe Wang received the B.Eng. degree from the Southeast University, China, in 2010, the M.Eng. degree from the Beihang University, China, in 2013, and the Ph.D. degree from the Nanyang Technological University (NTU), Singapore, in 2019. He is a Research Fellow in the School of Electrical and Electronic Engineering, NTU. He has served as an Associate Editor for The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) from 2020 to 2022. His current research interests include mobile robotics, control application, and cybersecurity in robotics. Danwei Wang received his Ph.D. and M.S.E. degrees from the University of Michigan, Ann Arbor in 1989 and 1984, respectively. He received his B.E. degree from the South China University of Technology, China, in 1982. He is a Professor in the School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore. He has served as the Head of the Division of Control and Instrumentation, NTU from 2005 to 2011, the Director of the Center for System Intelligence and Efficiency, NTU from 2014 to 2016, and the Director of the ST Engineering-NTU Corporate Laboratory, NTU from 2015 to 2021. He also served as general chairman, technical chairman and various positions in several international conferences. He was a recipient of Alexander von Humboldt fellowship, Germany. He is a Fellow of Academy of Engineering, Singapore, and a Fellow of IEEE. His research interests include robotics, control engineering, and fault diagnosis.
Content
Health Monitoring of Engineering Systems.- Hybrid Systems and Hybrid Bond Graph Models.- Quantitative Hybrid Bond Graph-based Fault Detection and Isolation.- Fault Identification Techniques.- Mode Tracking Techniques.- Application of Real Time FDI and Fault Estimation to a Vehicle Steering System.- Multiple Failure Prognosis for Hybrid Systems.