2020•Journal of Physics Conference SeriesOpen access

Research on fault diagnosis method of 750kV substation based on Bayesian network and fault recording information fusion

Poli Shang, Haiying Dong, Xiaonan Li, Wei Ren

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Abstract

Abstract Aiming at the complexity of the 750kV substation system and the uncertainty of the fault information, this paper studies the fault diagnosis method of Bayesian network and fault recording information. In order to solve the problem of single-source, DS evidence theory is used to fuse the two diagnosis results. Through case analysis, it is proved that the method can effectively improve the accuracy of fault diagnosis.

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What this paper is about

Abstract Aiming at the complexity of the 750kV substation system and the uncertainty of the fault information, this paper studies the fault diagnosis method of Bayesian network and fault recording information. In order to solve the problem of single-source, DS evidence theory is used to fuse the two diagnosis results. Through case analysis, it is proved that the method can effectively improve the accuracy of fault diagnosis.

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Available abstract

Abstract Aiming at the complexity of the 750kV substation system and the uncertainty of the fault information, this paper studies the fault diagnosis method of Bayesian network and fault recording information. In order to solve the problem of single-source, DS evidence theory is used to fuse the two diagnosis results. Through case analysis, it is proved that the method can effectively improve the accuracy of fault diagnosis.

Key concepts: Fuse (electrical), Fault (geology), Bayesian network, Information fusion, Computer science, Bayesian probability, Data mining, Reliability engineering

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