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ABSTRACT
A dynamic system constantly evolves between functioning modes which are either normal or faulty due to the existence of a defect. Failure diagnosis consists in detecting such defects and localizing their origin by comparing instant information generated by the system to a standard or model representing the normal and/or faulty functioning. Models based upon “discrete” events are used for studies focused on particular instants of the state of the system. The various diagnoses of discrete event systems (DESs) methods are the subject of studies and comparisons; they are also classified according to several criteria, their advantages and limits.
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Moamar SAYED MOUCHAWEH: University of Reims, ICST Research Center (URCA-CReSTIC)
INTRODUCTION
A dynamic system is likely to evolve between normal and faulty operating modes. A faulty operating mode is reached when a fault occurs.
Fault diagnosis is defined as the operation used to detect a fault and locate its origin. Diagnosis involves comparing instantaneous information from the system with a reference or model representing normal and/or faulty operation.
Discrete-event models are used when we are only interested in particular instants of the system state (events corresponding, for example, to the start and end of operations, or the occurrence of faults).
In this article, different methods for diagnosing Discrete Event Systems (DES) are studied and classified according to different criteria. Their advantages, as well as their limitations, are then presented in order to explore the complementarity between these methods.
Numerous examples are used to illustrate how these methods work.
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Discrete-event system (DES) diagnostics
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