Overview
- Offers in-depth comprehensive study on health monitoring for hybrid systems
- Includes new concepts, such as GARR, mode tracking and multiple failure prognosis
- Contains many examples, making the developed techniques easily understandable and accessible
- Introduces state-of-the-art algorithms and methodologies from experienced researchers
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Table of contents (7 chapters)
Keywords
- Bond Graph
- Failure Prognosis
- Fault Detection and Isolation
- Fault Diagnosis
- Global Analytical Redundancy Relations
- Hybrid Bond Graph
- Hybrid Systems
- Mode Tracker
- Model-based Health Monitoring
- Remaining Useful Life
- Sequential Causality Assignment Procedure for Hybrid Systems
- Vehicle Steering System
- complexity
About this book
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.Authors and Affiliations
Bibliographic Information
Book Title: Model-based Health Monitoring of Hybrid Systems
Authors: Danwei Wang, Ming Yu, Chang Boon Low, Shai Arogeti
DOI: https://doi.org/10.1007/978-1-4614-7369-5
Publisher: Springer New York, NY
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Science+Business Media New York 2013
Hardcover ISBN: 978-1-4614-7368-8
Softcover ISBN: 978-1-4899-9059-4
eBook ISBN: 978-1-4614-7369-5
Edition Number: 1
Number of Pages: XII, 297
Topics: System Performance and Evaluation, Control and Systems Theory, Complexity, Robotics and Automation