Model-Based Fault Diagnosis Techniques

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Sprache: Englisch

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Beschreibung

Guaranteeing a high system performance over a wide operating range is an important issue surrounding the design of automatic control systems with successively increasing complexity. As a key technology in the search for a solution, advanced fault detection and identification (FDI) is receiving considerable attention. This book introduces basic model-based FDI schemes, advanced analysis and design algorithms, and mathematical and control-theoretic tools.
This second edition of Model-Based Fault Diagnosis Techniques contains:
¿ new material on fault isolation and identification and alarm management;
¿ extended and revised treatment of systematic threshold determination for systems with both deterministic unknown inputs and stochastic noises;
¿ addition of the continuously-stirred tank heater as a representative process-industrial benchmark; and
¿ enhanced discussion of residual evaluation which now deals with stochastic processes.
Model-based Fault Diagnosis Techniques will interest academic researchers working in fault identification and diagnosis and as a text it is suitable for graduate students in a formal university-based course or as a self-study aid for practising engineers working with automatic control or mechatronic systems from backgrounds as diverse as chemical process and power engineering.

Über den Autor

Steven X. Ding began investigating issues concerned with model-based fault detection and identification in 1986 during his PhD. Following a three-year stay in industry, in which he gained experience with the application of FDI techniques in real technical processes, he returned to academia and during the last 17 years has become a university professor and institute head. He has been involved with numerous national and international research grants and industrial projects in the development of advanced FDI methods and their application in different sectors of industry. He teaches fault diagnosis and fault-tolerant systems to Masters students and advanced FDI methods to PhD students at the University of Duisburg-Essen. He has also guest-lectured and taught courses on these subjects at other universities and research institutes. Professor Ding has published more than 80 journal and 130 conference papers associated with the field of FDI.

Zusammenfassung

Gives readers a framework of model-based FDI techniques, helping them to become familiar with the basic ideas and schemes in a systematic way

Design algorithms and mathematical and control engineering tools encourage the translation of the ideas of the book to readers' own systems

Examples and benchmarks provide a means of practising the ideas and judging the methods described

Classroom tested in the author's teaching of graduate students

Includes supplementary material: [...]

Inhaltsverzeichnis

Basic Ideas, Major Issues, and Tools in the Observer-Based FDI Framework.- Modelling of Technical Systems.- Structural Fault Detectability, Isolability and Identifiability.- Basic Residual Generation Methods.- Perfect Unknown Input Decoupling.- Residual Generation with Enhanced Robustness against Unknown Inputs.- Residual Generation with Enhanced Robustness against Model Uncertainties.- Norm-Based Residual Evaluation and Threshold Computation.- Statistical-Methods-Based Residual Evaluation and Threshold Setting.- Integration of Norm-Based and Statistical Methods.- Integrated Design of Fault Detection Systems.- Fault Isolation Schemes.

Details

Erscheinungsjahr:	2015
Fachbereich:	Nachrichtentechnik
Genre:	Importe , Technik
Rubrik:	Naturwissenschaften & Technik
Medium:	Taschenbuch
Inhalt:	xx 504 S.
ISBN-13:	9781447161110
ISBN-10:	1447161114
Sprache:	Englisch
Einband:	Kartoniert / Broschiert
Autor:	Ding, Steven X.
Auflage:	2nd edition 2013
Hersteller:	Springer London
Verantwortliche Person für die EU:	Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße:	235 x 155 x 29 mm
Von/Mit:	Steven X. Ding
Erscheinungsdatum:	28.01.2015
Gewicht:	0,785 kg

Artikel-ID: 104907092