The Fault Diagnosis Method for Electrical Equipment Using Bayesian Network

被引:1
|
作者
Wang Yongqiang [1 ]
Lu Fangcheng [1 ]
Li Heming [1 ]
机构
[1] N China Elect Power Univ, Dept Elect Engn, Baoding, Hebei Province, Peoples R China
来源
PROCEEDINGS OF THE FIRST INTERNATIONAL WORKSHOP ON EDUCATION TECHNOLOGY AND COMPUTER SCIENCE, VOL II | 2009年
关键词
Bayesian network; model; electrical equipment; fault diagnosis;
D O I
10.1109/ETCS.2009.386
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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 eqipment. But, it's very difficult to exact diagnosis the fault because power transformer's 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 transformer 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.
引用
收藏
页码:563 / 565
页数:3
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