Transformer Fault Diagnosis Based on rough sets and support vector machine

被引：0

作者：

Li Zhi-bin ^{[1
]}

Xie Zhi-hui ^{[1
]}

机构：

[1] Shanghai Univ Elect Power, Coll Power & Automat, Shanghai, Peoples R China

来源：

2012 ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC) | 2012年

关键词：

transformer; fault diagnosis; rough sets; support vector machine;

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：

For the problem of little sample size and incomplete sample information which leads to the fact that fault diagnosis results are not ideal in the transformer fault diagnosis process, we combine the simplifying of rough sets with support vector machine classification. Then, we build the model of transformer fault diagnosis which is based on the rough sets and support vector machine. Proved by the simulation of true sample, this model can diagnosis the transformer fault effectively and has very high accuracy rate.

引用

页数：4