2020
DOI: 10.1109/access.2020.2986306
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A Fuzzy Petri-Net Approach for Fault Analysis Considering Factor Influences

Abstract: In fault analysis or diagnosis, we not only need to assess the possibility of a fault but also need to know the impacts of various casual factors on the possible outcome of the fault. A fuzzy Petri net (FPN) has the advantage of knowledge representation and fuzzy reasoning and may become a powerful fault analysis tool. Current FPNs and reasoning algorithms, however, do not reflect the influence of the causes on the results. Based on the weighted fuzzy Petri net, an enhanced weighted fuzzy Petri net (EWFPN) as … Show more

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Cited by 15 publications
(4 citation statements)
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“…Petri-net (PN) is a very effective modelling technique that uses graphic symbols like places, arcs and transitions to highlight the mutual effect and interrelationship of parts and movement of tokens to show the state change (Zhou, 2020). After introducing fuzzy rule-based structures in PN, practitioners and academics in different fields gained broad attention.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Petri-net (PN) is a very effective modelling technique that uses graphic symbols like places, arcs and transitions to highlight the mutual effect and interrelationship of parts and movement of tokens to show the state change (Zhou, 2020). After introducing fuzzy rule-based structures in PN, practitioners and academics in different fields gained broad attention.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Yvonne Power et al used Petri nets based on real-time data to locate a specific part of the device where the fault occurred [7]. JIANFENG ZHOU proposed an enhanced weighted fuzzy Petri net and its inference algorithm, which is characterized by the use of matrix to represent the interaction between markers and places [8]. Changan Wang proposed an adaptive neuro-fuzzy Petri net algorithm based on the traditional Petri net theory to solve the uncertainty of fault propagation [9].…”
Section: Introductionmentioning
confidence: 99%
“…In recent years, equipment support researchers have adopted a variety of modeling methods to describe the maintenance support process of equipment [6,7], such as Petri net model [8][9][10] adopted by many scholars, expert knowledge system model [11], proportional hazards model [12], wiener process model [13], stochastic model [14], deep learning model [15], neural networks model [16], and fuzzy logic model [17].…”
Section: Introductionmentioning
confidence: 99%