Transformers fault diagnosis based on artificial neural network

被引：0
|
作者：
Tu, YM
Quan, YS
Yan, Z
机构：
来源：
JOINT CONFERENCE OF 96' AICDEI / 4T-JCCEID | 1996年
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
An artificial neural network (ANN) approach to detect faults in oil-filled power transformers is presented in this paper. ANN can learn and adapt to statistical distributions, extract essential characteristic from input data. A lot of the sample transformer data sets are learned by the neural networks. After the learning process is over, it is able to apply the knowledge to make reasonable generalization on unknown input patterns. The results show that this method is feasible.
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收藏
页码：393 / 396
页数：4
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