DocumentCode
3600378
Title
The Fault Diagnosis Method for Electrical Equipment Using Bayesian Network
Author
Yongqiang, Wang ; Fangcheng, Lu ; Heming, Li
Author_Institution
Dept. of Electr. Eng., North China Electr. Power Univ., Baoding
Volume
2
fYear
2009
Firstpage
563
Lastpage
565
Abstract
Bayesian network offers a powerful map framework that can process probabilities inference. It can be used in inference and express of uncertainty knowledge. This paper introduce a new electrical equipment fault diagnosis method based on Bayesian network (BN). For example, power transformer is very important in power system as a electrical equipment. But, itpsilas very difficult to exact diagnosis the fault because power transformerpsilas complexity configuration. Now, dissolved gas analysis (DGA) is the most effective and convenient method in transformer fault diagnosis. However, the codes of DGA is too absolute, so this paper advances a new trans-former fault diagnosis method based on Bayesian network (BN). This method introduces BN method into transformer fault diagnosis and presents a new idea of finding out transformer faults rapidly and exactly. Finally, the application examples in the fault diagnosis of transformer are given which shows that this method is effective.
Keywords
belief networks; chemical analysis; power apparatus; power transformers; Bayesian network; dissolved gas analysis; electrical equipment; fault diagnosis method; power transformer; uncertainty knowledge; Bayesian methods; Computer science education; Dissolved gas analysis; Educational technology; Fault diagnosis; Power engineering education; Power system analysis computing; Power system faults; Power transformers; Uncertainty; Bayesian network; electrical equipment; fault diagnosis; model;
fLanguage
English
Publisher
ieee
Conference_Titel
Education Technology and Computer Science, 2009. ETCS '09. First International Workshop on
Print_ISBN
978-1-4244-3581-4
Type
conf
DOI
10.1109/ETCS.2009.386
Filename
4959101
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