Advanced methods for fault diagnosis and fault-tolerant control / Steven X. Ding.
Ding, Steven X., author.
2020
TA169.6
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Title
Advanced methods for fault diagnosis and fault-tolerant control / Steven X. Ding.
Author
Ding, Steven X., author.
ISBN
9783662620045 (electronic bk.)
3662620049 (electronic bk.)
9783662620038
DOI
https://doi.org/10.1007/978-3-662-62004-5
Published
Berlin : Springer, [2020]
Language
English
Description
1 online resource (664 pages)
Item Number
10.1007/978-3-662-62004-5 doi
Call Number
TA169.6
Dewey Decimal Classification
629.8
Summary
After the first two books have been dedicated to model-based and data-driven fault diagnosis respectively, this book addresses topics in both model-based and data-driven thematic fields with considerable focuses on fault-tolerant control issues and application of machine learning methods. The major objective of the book is to study basic fault diagnosis and fault-tolerant control problems and to build a framework for long-term research efforts in the fault diagnosis and fault-tolerant control domain. In this framework, possibly unified solutions and methods can be developed for general classes of systems. The book is composed of six parts. Besides Part I serving as a common basis for the subsequent studies, Parts II - VI are dedicated to five different thematic areas, including model-based fault diagnosis methods for linear time-varying systems, nonlinear systems and systems with model uncertainties, statistical and data-driven fault diagnosis methods, assessment of fault diagnosis systems, as well as fault-tolerant control with a strong focus on performance degradation monitoring and recovering. These parts are self-contained and so structured that they can also be used for self-study on the concerned topics. The content Basic requirements on fault detection and estimation Basic methods for fault detection and estimation in static and dynamic processes Feedback control, observer, and residual generation Fault detection and estimation for linear time-varying systems Detection and isolation of multiplicative faults in uncertain systems Analysis, parameterisation and optimal design of nonlinear observer-based fault detection systems Data-driven fault detection methods for large-scale and distributed systems Alternative test statistics and data-driven fault detection methods Application of randomised algorithms to assessment and design of fault diagnosis systems Performance-based fault-tolerant control Performance degradation monitoring and recovering Data-driven fault-tolerant control schemes The target groups This book would be valuable for graduate and PhD students as well as for researchers and engineers in the field. The author Prof. Dr.-Ing. Steven X. Ding is a professor and the head of the Institute for Automatic Control and Complex Systems (AKS), University of Duisburg-Essen, Germany. His research interests are model-based and data-driven fault diagnosis, control and fault-tolerant systems as well as their applications in industry with a focus on automotive systems, chemical processes and renewable energy systems.
Bibliography, etc. Note
Includes bibliographical references and index.
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Description based on print version record.
Available in Other Form
Advanced Methods for Fault Diagnosis and Fault-Tolerant Control.
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Intro
Notation
Preface
Contents
Part I Introduction, Basic Concepts and Preliminaries
1 Introduction
1.1 Trends and Mainstream in Research
1.1.1 Data-Driven, Statistic and Machine Learning Based Fault Diagnosis Methods
1.1.2 Model-Based Fault Diagnosis Research
1.1.3 Detection of Intermittent and Incipient Faults
1.1.4 Fault-Tolerant Control
1.2 Motivation
1.2.1 Data-Driven and Model-Based Fault Diagnosis
1.2.2 Fault-Tolerant Control and Performance Degradation Recovery
1.2.3 Performance Assessment of Fault Diagnosis and Fault-Tolerant control Systems

1.3 Outline of the Contents
1.3.1 Part I: Introduction, Basic Concepts and Preliminaries
1.3.2 Part II: Fault Detection, Isolation and Estimation in Linear dynamic Systems
1.3.3 Part III: Fault Detection in Nonlinear Dynamic Systems
1.3.4 Part IV: Statistical and Data-Driven Fault Diagnosis Methods
1.3.5 Part V: Application of Randomised Algorithms to Assessment and Design of Fault Diagnosis Systems
1.3.6 Part VI: An Integrated Framework of Control and Diagnosis, And fault-Tolerant Control Schemes
1.4 Notes and References
References

2 Basic Requirements on Fault Detection and Estimation
2.1 Fault Detection and Estimation Paradigm
2.2 Fault Detection and Estimation in the Probabilistic Framework
2.2.1 Fault Detection Performance Assessment
2.2.2 Optimal Fault Detection and Estimation Problems
2.3 Fault Detection and Estimation in Deterministic Processes
2.3.1 Performance Assessment
2.3.2 Characterisation of Optimal Solutions
2.3.3 A General Form of Problem Formulation
2.4 Notes and References
References
3 Basic Methods for Fault Detection and Estimation in Static Processes

3.1 A Basic Fault Detection and Estimation Problem
3.2 A General Form of Fault Detection and Estimation Problem
3.3 Application of Canonical Correlation Analysis to Fault Detection
3.3.1 An Introduction to CCA
3.3.2 Application to Fault Detection and Estimation
3.3.3 CCA and GLR
3.4 Fault Detection and Estimation with Deterministic Disturbances
3.4.1 A Basic Fault Detection Problem
3.4.2 A General Form of Fault Detection and Estimation
3.5 The Data-Driven Solutions of the Detection and Estimation Problems

3.5.1 Fault Detection and Estimation in Statistic Processes with sufficient Training Data
3.5.2 Fault Detection Using Hotelling's T2 test statistic
3.5.3 Fault Detection Using Q Statistic
3.5.4 Application of Principal Component Analysis to Fault Diagnosis
3.5.5 LS, PLS and CCA
3.6 Notes and References
References
4 Basic Methods for Fault Detection in Dynamic Processes
4.1 Preliminaries and Review of Model-Based Residual Generation Schemes
4.1.1 Nominal System Models
4.1.2 Observer-Based Residual Generation Schemes
4.1.3 Parity Space Approach

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