ANN based transformer fault diagnosis

被引：0
|
作者：
Wang, ZY
Zhang, YW
Li, C
Liu, YL
机构：
来源：
PROCEEDINGS OF THE AMERICAN POWER CONFERENCE, VOL 59, I AND II | 1997年 / 59卷
关键词：
transformer fault diagnosis; artificial neural network; dissolved gas-in-oil analysis (DGA);
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：
This paper presents a further study on artificial neural network (ANN) approach for transformer fault diagnosis using dissolved gas-in-oil analysis (DGA) as additional data becomes available. The influence ofCO, CO2 concentrations on major fault diagnosis is clarified. An optimal ANN topology for major fault diagnosis is obtained on a trial basis. Preliminary study results show that information of gas generation rate can increase the accuracy of ANN based fault diagnosis and prediction.
引用
收藏
页码：428 / 432
页数：5
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