Power transformer fault diagnosis based on rough set theory and support vector machines

被引：0
|
作者：
Wu, Zhong-Li [1 ]
Yang, Jian [1 ]
Zhu, Yong-Li [1 ]
Liu, Zhu [1 ]
机构：
[1] School of Electrical and Electric Engineering, North China Electric Power University, Baoding 071003, China
来源：
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | 2010年 / 38卷 / 18期
关键词：
Power transformers - Support vector machines - Failure analysis - Fault detection - Mapping;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
A model for the location of the transformer fault diagnosis is built based on rough sets and support vector machine. Firstly, the results of the oil data and the electrical experimental data are combined and reduced based on rough set theory, so the mapping of the faults and the information is established. Then the mapping is classified by the support vector machine classifier, so the rough faulty point of the transformer is diagnosed. Examples show that the proposed diagnosis model can get the rough faulty point of the transformer with a satisfactory accuracy.
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页码：80 / 83
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