Diagnosis of Active Systems : Principles and Techniques (Kluwer International Series in Engineering and Computer Science)

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Diagnosis of Active Systems : Principles and Techniques (Kluwer International Series in Engineering and Computer Science)

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  • 製本 Hardcover:ハードカバー版／ページ数 460 p.
  • 言語 ENG
  • 商品コード 9781402074875
  • DDC分類 006.33

Full Description

This book is about model-based diagnosis of a class of discrete-event systems called active systems. Roughly, model-based diagnosis is the task of finding out the faulty components of a physical system based on the observed behavior and the system model. An active system is the abstraction of a physical artefact that is modeled as a network of com­ municating automata. For example, the protection apparatus of a power transmission network can be conveniently modeled as an active system, where breakers, protection devices, and lines are naturally described by finite state machines. The asynchronous occurrence of a short circuit on a line or a bus-bar causes the reaction of the protection devices, which aims to isolate the shorted line. This reaction can be faulty and several lines might be eventually isolated, rather than the shorted line only. The diagnostic problem to be solved is uncovering the faulty devices based the visible part of the reaction. Once the diagnosis task has been on accomplished, the produced results are exploited to fix the apparatus (and also to localize the short circuit, in this sample case). Interestingly, the research presented in this book was triggered a decade ago by a project 011 short circuit localization, conducted by ENEL, the Italian electricity board, along with other industrial and academic European partners.

Contents

I Background.- 1. Model-Based Diagnosis.- 2. Diagnosis of Discrete-Event Systems.- II Diagnosis of Active Systems.- 3. Active Systems.- 4. Monolithic Diagnosis.- 5. Modular Diagnosis.- III Polymorphic Systems.- 6. Simulation-Based Diagnosis.- 7. Rule-Based Diagnosis.- 8. Monitoring-Based Diagnosis.- IV Advanced Topics.- 9. Uncertain Observations.- 10. Complex Observations.- 11. Uncertain Events.- 12. Distributed Observations.- 13. Sample Application.- References.