Fault diagnosis method based on Petri nets considering service feature of information source devices

Cheng, Hongbo; He, Zhengyou; Wang, Qi; Yang, Jianwei; Lin, Senshang

doi:10.1016/j.compeleceng.2015.06.016

Cited by 17 publications

(10 citation statements)

References 11 publications

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“…PNs have been used by Mansour et al (2013) for fault diagnosis of large power generation station. To improve the confidence degree on the diagnostic result, Cheng et al (2015) proposed a method based on fuzzy PNs.…”

Section: Applications As Standalone Approachesmentioning

confidence: 99%

Applications of Bayesian networks and Petri nets in safety, reliability, and risk assessments: A review

2019

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System safety, reliability and risk analysis are important tasks that are performed throughout the system lifecycle to ensure the dependability of safety-critical systems. Probabilistic risk assessment (PRA) approaches are comprehensive, structured and logical methods widely used for this purpose. PRA approaches include, but not limited to, Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA), and Event Tree Analysis (ETA). Growing complexity of modern systems and their capability of behaving dynamically make it challenging for classical PRA techniques to analyse such systems accurately. For a comprehensive and accurate analysis of complex systems, different characteristics such as functional dependencies among components, temporal behaviour of systems, multiple failure modes/states for components/systems, and uncertainty in system behaviour and failure data are needed to be considered. Unfortunately, classical approaches are not capable of accounting for these aspects. Bayesian networks (BNs) have gained popularity in risk assessment applications due to their flexible structure and capability of incorporating most of the above mentioned aspects during analysis. Furthermore, BNs have the ability to perform diagnostic analysis. Petri Nets are another formal graphical and mathematical tool capable of modelling and analysing dynamic behaviour of systems. They are also increasingly used for system safety, reliability and risk evaluation. This paper presents a review of the applications of Bayesian networks and Petri nets in system safety, reliability and risk assessments. The review highlights the potential usefulness of the BN and PN based approaches over other classical approaches, and relative strengths and weaknesses in different practical application scenarios.

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Section: Applications As Standalone Approachesmentioning

confidence: 99%

Applications of Bayesian networks and Petri nets in safety, reliability, and risk assessments: A review

2019

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“…PN has characteristics of parallel information processing and concurrent operating function, so it is considered as a suitable and useful modeling tool [1]. Fault diagnosis methods based on PN or fuzzy PN (FPN) have good application cases in power systems [1][2][3][4]. For instance, a simplified fault diagnosis method based on PN for a large power generation station is proposed in Ref.…”

Section: Introductionmentioning

confidence: 99%

“…Further, the method proposed in Ref. [4] combines FPN with the reliability, and thus the service feature of information source devices can be represented.…”

Section: Introductionmentioning

confidence: 99%

Fault diagnosis model based on Bayesian network considering information uncertainty and its application in traction power supply system

Lin

Chen

Wang

2018

IEEJ Transactions Elec Engng

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Fault diagnosis is of great significance in maintaining the safe and stable operation of a system. Fast and precise location of faults is important for restoring power supply systems. In this paper, considering the interference of information uncertainty to fault diagnosis under different weather conditions, a fault diagnosis model based on Bayesian network is proposed. The model inherits the capability of processing uncertain information of a Bayesian network and divides the information into historical information and evidence information. The uncertainty of historical information is reduced by modifying the parameters through improving parameter learning formulas, while that of evidence information can be reduced by logical judgment. A fault simulation model based on Monte Carlo method is used to generate simulation data for parameter learning, and a case study confirms the correctness of the proposed fault diagnosis and fault simulation models.

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“…Many methods have been proposed for power grid fault diagnosis, including expert systems [1], analytic models [2,3], artificial neural networks [4], Bayesian networks [5], data mining technology [6], rough sets [7], and Petri nets [8][9][10][11][12][13]. In particular, fault diagnosis methods based on Petri nets have been attracting attention because of their rigorous logic, clear physical meaning, and simple reasoning process [8].…”

Section: Introductionmentioning

confidence: 99%

“…In [11], time constraints between power system failure events are used in a fuzzy Petri net (FPN) for fault diagnosis, which improves how the model reflects the actual fault process. To determine the initial position and the weights for a Petri net, a method was proposed in [12] for computing the deterministic factor and the weight of the initial position of the Petri net by using information source reliability. In [13], a fault diagnosis model that improves the adaptability of the model to different network topologies was presented, using Petri nets to integrate the power network topology, protection relays, and alarm information.…”

Section: Introductionmentioning

confidence: 99%

Method of power grid fault diagnosis using intuitionistic fuzzy Petri nets

Zhang

Yue

Zha

2017

IET Generation, Transmission & Distribution

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Fault diagnosis method based on Petri nets considering service feature of information source devices

Cited by 17 publications

References 11 publications

Applications of Bayesian networks and Petri nets in safety, reliability, and risk assessments: A review

Applications of Bayesian networks and Petri nets in safety, reliability, and risk assessments: A review

Fault diagnosis model based on Bayesian network considering information uncertainty and its application in traction power supply system

Method of power grid fault diagnosis using intuitionistic fuzzy Petri nets

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