Diagnosis of DGA based on fuzzy and ANN methods

被引：10

作者：

Gao, N ^{[1
]}

Zhang, GJ ^{[1
]}

Qian, Z ^{[1
]}

Yan, Z ^{[1
]}

Zhu, DH ^{[1
]}

机构：

[1] Tsing Hua Univ, Dept Elect Engn, Beijing 100084, Peoples R China

来源：

1998 INTERNATIONAL SYMPOSIUM ON ELECTRICAL INSULATING MATERIALS, PROCEEDINGS | 1998年

关键词：

insulation diagnosis; artificial neural network; Fuzzy Theory; principal component analysis;

D O I：

10.1109/ISEIM.1998.741860

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：

The accuracy of diagnosis with DGA(Dissolved Gas Analysis) is not satisfied though it is used widely in oil-immersed insulation. In this paper, the FART (Fuzzy Adaptive Resonance Theory) network is constructed to enhance the diagnostic accuracy of DGA method. Two input manners are discussed, one is the membership function of dissolved gases based on statistic method, another is the principal component analysis method. Finally, the practical examples had been given for checking the results of insulation diagnosis, it is shown that with the method introduced, the diagnosis will be more effective.

引用

页码：767 / 770

页数：4

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