Title :
The fault diagnosis method for power transformer based on BN And DGA
Author :
Yongqiang, Wang ; Fangcheng, Lu ; Heming, Li ; Yanqing, Li
Author_Institution :
Sch. of Electr. Eng., North China Electr. Power Univ., Baoding, China
Abstract :
Power transformer is very important in power system. Now, dissolved gas analysis (DGA) is the most effective and convenient method in transformer fault diagnosis. This paper advances a new transformer fault diagnosis method based on Bayesian network (BN) and dissolved gas analysis technique. And it constructs the transformer fault diagnosis model based on Bayesian network. Finally, the application examples in the fault diagnosis of transformer are given which shows that this method is effective.
Keywords :
belief networks; chemical analysis; fault diagnosis; insulation testing; power transformer insulation; power transformer testing; transformer oil; Bayesian network; DGA; dissolved gas analysis; power transformer; transformer fault diagnosis; transformer oil; Bayesian methods; Dissolved gas analysis; Fault diagnosis; Gases; Oil insulation; Petroleum; Power system analysis computing; Power system faults; Power system modeling; Power transformers;
Conference_Titel :
Electrical Insulating Materials, 2005. (ISEIM 2005). Proceedings of 2005 International Symposium on
Print_ISBN :
4-88686-063-X
DOI :
10.1109/ISEIM.2005.193592
