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Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems gives a systematic description of the many facets of envisaging, designing, implementing, and experimentally exploring emerging trends in fault diagnosis and failure prognosis in mechanical, electrical, hydraulic and biomedical systems. The book is devoted to the development of mathematical methodologies for fault diagnosis and isolation, fault tolerant control, and failure prognosis problems of engineering systems. Sections present new techniques in reliability modeling, reliability analysis, reliability design, fault and failure detection, signal processing, and fault tolerant control of engineering systems.
Sections focus on the development of mathematical methodologies for diagnosis and prognosis of faults or failures, providing a unified platform for understanding and applicability of advanced diagnosis and prognosis methodologies for improving reliability purposes in both theory and practice, such as vehicles, manufacturing systems, circuits, flights, biomedical systems. This book will be a valuable resource for different groups of readers – mechanical engineers working on vehicle systems, electrical engineers working on rotary machinery systems, control engineers working on fault detection systems, mathematicians and physician working on complex dynamics, and many more.
- Presents recent advances of theory, technological aspects, and applications of advanced diagnosis and prognosis methodologies in engineering applications
- Provides a series of the latest results, including fault detection, isolation, fault tolerant control, failure prognosis of components, and more
- Gives numerical and simulation results in each chapter to reflect engineering practices
Researchers, graduates, and post-graduate students on mechanical engineering, electrical engineering, control engineering, mechatronics, applied mathematics; and physician
1. Quality-related Fault Detection and Diagnosis-A Technical Review and Summary
2. Fault diagnosis and failure prognosis in hydraulic systems
3. Canonical correlation analysis-based fault diagnosis method for dynamic processes
4. H-infinity fault estimation for linear discrete time-varying systems with random uncertainties
5. Intelligent Fault Diagnosis for Dynamic Systems via Extended State Observer and Soft Computing
6. Fault Detection and Fault Identification in Marine Current Turbines
7. Quadrotor Actuator Fault Diagnosis and Accommodation based on Nonlinear Adaptive State Observer
8. Defect Detection and Classification in Welding Using Deep Learning and Digital Radiography
9. Deep learning based fault diagnosis for rotationary machines
10. Fault diagnosis and failure prognosis of electrical machines and drives
- No. of pages:
- © Academic Press 2021
- 1st June 2021
- Academic Press
- Paperback ISBN:
Dr. Karimi received the B.Sc. (First Hons.) degree in power systems from the Sharif University of Technology, Tehran, Iran, in 1998, and the M.Sc. and Ph.D. (First Hons.) degrees in control systems engineering from the University of Tehran, Tehran, in 2001 and 2005, respectively. His research interests are in the areas of control systems/theory, mechatronics, networked control systems, intelligent control systems, signal processing, vibration control, ground vehicles, structural control, wind turbine control and cutting processes. He is an Editorial Board Member for some international journals and several Technical Committee. Prof. Karimi has been presented a number of national and international awards, including Alexander-von-Humboldt Research Fellowship Award (in Germany), JSPS Research Award (in Japan), DAAD Research Award (in Germany), August-Wilhelm-Scheer Award (in Germany) and been invited as visiting professor at a number of universities in Germany, France, Italy, Poland, Spain, China, Korea, Japan, India.
Professor of Applied Mechanics, Department of Mechanical Engineering, Politecnico di Milano, Milan, Italy
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