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Diagnosis of Partially Observed Petri Net Based on Analytical Redundancy Relationships
Author(s) -
Chouchane Amira,
Khedher Atef,
Nasri Othman,
Kamoun Anas
Publication year - 2019
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1832
Subject(s) - petri net , subnet , redundancy (engineering) , unobservable , computer science , algorithm , disjoint sets , fault (geology) , fault detection and isolation , reliability engineering , engineering , mathematics , discrete mathematics , artificial intelligence , computer network , actuator , seismology , econometrics , geology
In this paper, we design an efficient diagnosis technique for partially observed discrete event systems modeled by labeled Petri nets. The fault detection is based on analytical redundancy relationships derived from the nominal model. The decomposition of the T u n ‐induced subnet to connected subgraphs allows determining the subgraphs that may contain faults. To appreciate the fault localization, a set of analytical redundancy relationships is etablished for each fault transition based on the fault model. The proposed diagnosis approach is independent of the length of the observed sequence and independent of the number of unobservable transitions. The detected faults with the proposed approach are faults which led to a change in the number of tokens in the net.