Library Services | Technical University of Kenya

Your cart is empty.
Normal view MARC view ISBD view

Model-based Health Monitoring of Hybrid Systems [electronic resource] / by Danwei Wang, Ming Yu, Chang Boon Low, Shai Arogeti.

By: Wang, Danwei [author.].
Contributor(s): Yu, Ming [author.] | Low, Chang Boon [author.] | Arogeti, Shai [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: New York, NY : Springer New York : Imprint: Springer, 2013Description: XII, 297 p. 246 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9781461473695.Subject(s): Computer science | Computer system performance | Physics | Engineering | Computer Science | System Performance and Evaluation | Control | Complexity | Robotics and AutomationDDC classification: 004.24 Online resources: Click here to access online
Contents:
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.
In: Springer eBooksSummary: 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.
Tags from this library: No tags from this library for this title. Log in to add tags.
No physical items for this record

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.

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.

There are no comments for this item.

Log in to your account to post a comment.

2017 | The Technical University of Kenya Library | +254(020) 2219929, 3341639, 3343672 | library@tukenya.ac.ke | Haile Selassie Avenue