Safe diagnosis of pattern faults of stochastic discrete‐event systems and verification algorithm

Abstract In many real‐world applications, faults often result from specific events occurring in succession (i.e., pattern faults) rather than from a single failure event. This paper investigates the safe diagnosis of pattern faults in stochastic discrete‐event systems (SDESs). First, the notions of ‐type and ‐type pattern safe diagnosability for SDESs are formalized. Roughly speaking, a stochastic automaton is called ‐type (or ‐type) pattern safe diagnosable if the detection of ‐type (or ‐type) pattern faults is achieved with high probability (i.e., the probability of not detecting pattern faults is sufficiently low) before the system performs risky actions. The necessary and sufficient conditions for the pattern safe diagnosability of SDESs are then presented after constructing a pattern safe diagnoser and recognizer of a forbidden language from a given stochastic system. Consequently, an algorithm for verifying the pattern safe diagnosability of SDESs is proposed, demonstrating how the pattern‐safe diagnoser can be used for the safe diagnosis of pattern faults.

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Publication Details

Journal
Asian Journal of Control
Published
2024-12-03
DOI
https://doi.org/10.1002/asjc.3546
Primary Topic
Petri Nets in System Modeling
Type
article
Field-Weighted Citation Impact
0.00

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article

Safe diagnosis of pattern faults of stochastic discrete‐event systems and verification algorithm

Fuchun Liu, Hongzhen Zhu
Asian Journal of Control
Petri Nets in System Modeling
article

Safe diagnosis of pattern faults of stochastic discrete‐event systems and verification algorithm

Fuchun Liu, Hongzhen Zhu
article en

Abstract

Abstract In many real‐world applications, faults often result from specific events occurring in succession (i.e., pattern faults) rather than from a single failure event. This paper investigates the safe diagnosis of pattern faults in stochastic discrete‐event systems (SDESs). First, the notions of ‐type and ‐type pattern safe diagnosability for SDESs are formalized. Roughly speaking, a stochastic automaton is called ‐type (or ‐type) pattern safe diagnosable if the detection of ‐type (or ‐type) pattern faults is achieved with high probability (i.e., the probability of not detecting pattern faults is sufficiently low) before the system performs risky actions. The necessary and sufficient conditions for the pattern safe diagnosability of SDESs are then presented after constructing a pattern safe diagnoser and recognizer of a forbidden language from a given stochastic system. Consequently, an algorithm for verifying the pattern safe diagnosability of SDESs is proposed, demonstrating how the pattern‐safe diagnoser can be used for the safe diagnosis of pattern faults.

Asian Journal of ControlVol. 27(4)
Guangdong University of Technology (CN)
Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 74%
Petri Nets in System Modeling
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Safe diagnosis of pattern faults of stochastic discrete‐event systems and verification algorithm — Fuchun Liu, Hongzhen Zhu · Asian Journal of Control (2024) | TGRS Research Map | TGRS