The Application of Bayesian Network Theory in Transformer Condition Assessment

被引：0

作者：

Quan, Jiangtao ^{[1
]}

Ruan, Ling ^{[1
]}

Xie, Zhicheng ^{[2
]}

Li, Xingdong ^{[2
]}

Lin, Xiangning ^{[2
]}

机构：

[1] Hubei Elect Power Test & Res Inst, State Grid Key Lab Onsite Test Technol High Volta, Wuhan 430077, Peoples R China

[2] Huazhong Univ Sci & Technol, State Key Lab Adv Electromagnet Engn & Technol, Wuhan 430074, Peoples R China

来源：

2013 IEEE PES ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC) | 2013年

关键词：

Transformer's status; Fault diagnosis; Bayesian Network; NBC; TAN;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

In order to assess transformer's status and forecast its potential fault, this paper applied Bayesian network classifier into transformer fault diagnosis, combined with dissolved gas analysis and other electrical test results, and thereby created a transformer fault synthetic diagnosis method. Build up transformer's fault diagnosis model based on Naive Bayesian Classifier and Tree Augmented Naive Bayesian Classifier respectively, and verify their validity by instance.

引用

页数：4

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