Model-Based Fault Diagnosis (eBook)

This book investigates in detail model-based fault diagnosis methods, including observer-based residual generation, residual evaluation based on threshold computation, observer-based fault isolation strategies, observer-based fault estimation, Kalman filter-based fault diagnosis methods, and parity space approach. Studies on model-based fault diagnosis have attracted engineers and scientists from various disciplines, such as electrical, aerospace, mechanical, and chemical engineering. Pursuing a holistic approach, the book establishes a fundamental framework for this topic, while emphasizing the importance of state-space approach. The methods introduced in the book are systemic and easy to follow. The book is intended for undergraduate and graduate students who are interested in fault diagnosis and state estimation, researchers investigating fault diagnosis and fault-tolerant control, and control system design engineers working on safety-critical systems.

Dr. Zhenhua Wang received his B.Sc. degree from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2008 and his M.Sc. and Ph.D. degrees from Harbin Institute of Technology, Harbin, China, in 2010 and 2014, respectively. He is an associate professor with the Department of Control Science and Engineering at Harbin Institute of Technology. His research interests include fault diagnosis, set-membership estimation, and fault-tolerant control. Since 2012, Dr. Wang has published more than 30 peer-reviewed technical papers in international journals. He is a member of IEEE and served as a reviewer of several international journals and an IPC member of the 28th, 29th, 30th Mediterranean Conference on Control and Automation.  

Dr. Yi Shen received his B.Sc., M.Sc., and Ph.D. degrees from Harbin Institute of Technology in 1985, 1988, and 1995, respectively. He is a professor at Harbin Institute of Technology. His research interests include fault diagnosis, flight vehicle control, and ultrasound signal processing. 

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This book investigates in detail model-based fault diagnosis methods, including observer-based residual generation, residual evaluation based on threshold computation, observer-based fault isolation strategies, observer-based fault estimation, Kalman filter-based fault diagnosis methods, and parity space approach. Studies on model-based fault diagnosis have attracted engineers and scientists from various disciplines, such as electrical, aerospace, mechanical, and chemical engineering. Pursuing a holistic approach, the book establishes a fundamental framework for this topic, while emphasizing the importance of state-space approach. The methods introduced in the book are systemic and easy to follow. The book is intended for undergraduate and graduate students who are interested in fault diagnosis and state estimation, researchers investigating fault diagnosis and fault-tolerant control, and control system design engineers working on safety-critical systems.