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Diagnosability of Event Patterns in Safe Labeled Time Petri Nets: A Model-Checking Approach

Authors :
Audine Subias
Yannick Pencolé
Équipe DIagnostic, Supervision et COnduite (LAAS-DISCO)
Laboratoire d'analyse et d'architecture des systèmes (LAAS)
Université Toulouse Capitole (UT Capitole)
Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse)
Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J)
Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3)
Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP)
Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole)
Université de Toulouse (UT)
Institut National des Sciences Appliquées - Toulouse (INSA Toulouse)
Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)
Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1)
Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3)
Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse)
Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National Polytechnique (Toulouse) (Toulouse INP)
Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1)
Université Fédérale Toulouse Midi-Pyrénées
Institut National des Sciences Appliquées (INSA)
Source :
IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Automation Science and Engineering, 2022, 19 (2), pp.1151-1162. ⟨10.1109/TASE.2020.3045565⟩, IEEE Transactions on Automation Science and Engineering, Institute of Electrical and Electronics Engineers, In press, ⟨10.1109/TASE.2020.3045565⟩
Publication Year :
2022
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2022.

Abstract

International audience; Checking the diagnosability of a time discrete event system usually consists in determining whether a single fault event can always be identified with certainty after a finite amount of time. The aim of this paper is to extend this type of analysis to more complex behaviors, called event patterns, and to propose an effective method to check diagnosability with the use of modelchecking techniques. To do so, we propose to convert the pattern diagnosability problem into checking a linear-time property over a specific time Petri net. Note to Practitioners-This paper is motivated by the problem of improving the monitoring and the supervision of systems like automated and robotised manufacturing systems. Based on a model of the system, the paper proposes a method to assert with certainty whether the available set of sensors will always provide enough information to ensure that a complex and unexpected behavior has not happened in the system. The proposed method uses a publicly available model-checking tool to perform this analysis.

Details

ISSN :
15583783 and 15455955
Volume :
19
Database :
OpenAIRE
Journal :
IEEE Transactions on Automation Science and Engineering
Accession number :
edsair.doi.dedup.....42fc0290081d188891630b36902ad544