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Bridges between Diagnosis Theories from Control and AI Perspectives

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 230)

Abstract

Diagnosis is the process of identifying or determining the nature and root cause of a failure, problem, or disease from the symptoms arising from selected measurements, checks or tests. The different facets of the diagnosis problem and the wide spectrum of classes of systems make this problem interesting to several communities and call for bridging theories. This paper presents diagnosis theories proposed by the Control and the AI communities and exemplifies how they can be synergically integrated to provide better diagnostic solutions and to interactively contribute in fault management architectures.

Keywords

Model-based diagnosis data-based diagnosis Bridge diagnosis track abstractions learning diagnostic models fault management 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.CNRS, LAASToulouseFrance
  2. 2.Univ de Toulouse, LAASToulouseFrance

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