Fault Diagnosis for Discrete Event Systems Using Partially Observed Petri Nets

This study proposes a fault diagnosis method of discrete event systems on the basis of a Petri net model with partially observable transitions. Assume that the structure of the Petri net model and the initial marking are known, and the faults can be modeled by its unobservable transitions. One of th...

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Main Authors: Ye Dandan, Luo Jiliang, Su Hongye
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2020/2392904
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spelling doaj-5679a098d0de40e09983ee037ee37e162020-11-25T03:49:54ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472020-01-01202010.1155/2020/23929042392904Fault Diagnosis for Discrete Event Systems Using Partially Observed Petri NetsYe Dandan0Luo Jiliang1Su Hongye2State Key Laboratory of Industrial Control Technology and Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, ChinaCollege of Information Science and Engineering, Huaqiao University, Xiamen, ChinaState Key Laboratory of Industrial Control Technology and Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, ChinaThis study proposes a fault diagnosis method of discrete event systems on the basis of a Petri net model with partially observable transitions. Assume that the structure of the Petri net model and the initial marking are known, and the faults can be modeled by its unobservable transitions. One of the contributions of this work is the use of the structure information of Petri net to construct an online fault diagnoser which can describe the system behavior of normal or potential faults. By modeling the flow of tokens in particular places that contain fault information, the variation of tokens in these places may be calculated. The outputs and inputs of these places are determined to be enabled or not through analyzing some special structures. With the structure information, traversing all the states is not required. Furthermore, the computational complexity of the polynomial allows the model to meet real-time requirements. Another contribution of this work is to simplify the subnet model ahead of conducting the diagnostic process with the use of reduction rules. By removing some nodes that do not contain the necessary diagnostic information, the memory cost can be reduced.http://dx.doi.org/10.1155/2020/2392904
collection DOAJ
language English
format Article
sources DOAJ
author Ye Dandan
Luo Jiliang
Su Hongye
spellingShingle Ye Dandan
Luo Jiliang
Su Hongye
Fault Diagnosis for Discrete Event Systems Using Partially Observed Petri Nets
Mathematical Problems in Engineering
author_facet Ye Dandan
Luo Jiliang
Su Hongye
author_sort Ye Dandan
title Fault Diagnosis for Discrete Event Systems Using Partially Observed Petri Nets
title_short Fault Diagnosis for Discrete Event Systems Using Partially Observed Petri Nets
title_full Fault Diagnosis for Discrete Event Systems Using Partially Observed Petri Nets
title_fullStr Fault Diagnosis for Discrete Event Systems Using Partially Observed Petri Nets
title_full_unstemmed Fault Diagnosis for Discrete Event Systems Using Partially Observed Petri Nets
title_sort fault diagnosis for discrete event systems using partially observed petri nets
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2020-01-01
description This study proposes a fault diagnosis method of discrete event systems on the basis of a Petri net model with partially observable transitions. Assume that the structure of the Petri net model and the initial marking are known, and the faults can be modeled by its unobservable transitions. One of the contributions of this work is the use of the structure information of Petri net to construct an online fault diagnoser which can describe the system behavior of normal or potential faults. By modeling the flow of tokens in particular places that contain fault information, the variation of tokens in these places may be calculated. The outputs and inputs of these places are determined to be enabled or not through analyzing some special structures. With the structure information, traversing all the states is not required. Furthermore, the computational complexity of the polynomial allows the model to meet real-time requirements. Another contribution of this work is to simplify the subnet model ahead of conducting the diagnostic process with the use of reduction rules. By removing some nodes that do not contain the necessary diagnostic information, the memory cost can be reduced.
url http://dx.doi.org/10.1155/2020/2392904
work_keys_str_mv AT yedandan faultdiagnosisfordiscreteeventsystemsusingpartiallyobservedpetrinets
AT luojiliang faultdiagnosisfordiscreteeventsystemsusingpartiallyobservedpetrinets
AT suhongye faultdiagnosisfordiscreteeventsystemsusingpartiallyobservedpetrinets
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