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Model-Based Fault Diagnosis Techniques: Design Schemes, Algorithms and Tools. 2nd ed. 2013
・ISBN 978-1-4471-4798-5 hard EUR 199.99
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お気に入り
★★★
| 著者・編者 | Ding, Steven X., |
|---|---|
| シリーズ | (Advances in Industrial Control) |
| 出版社 | (Springer London Ltd, UK) |
| 出版年月 | 2013 |
| ページ数 | 504 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A05-46040＞ |
解説
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.
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.