Dissolved gas analysis based on GA and FCM for power transformer fault diagnosis

被引：0

作者：

Nanjing University of Aeronautics and Astronautics, Nanjing 210006, China ^{[1
]}

不详 ^{[2
]}

机构：

来源：

Dianli Zidonghua Shebei / Electric Power Automation Equipment | 2008年 / 28卷 / 02期

关键词：

Clustering algorithms - Data reduction - Fuzzy clustering - Genetic algorithms;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

DGA (Dissolved Gas Analysis) is a method of power transformer fault diagnosis. Because the clustering center of FCM (Fuzzy C-Mean clustering algorithm) is difficult to determine and the local minimum occurs easily, a method, which combines the adaptive GA (Genetic Algorithm) and FCM together, is applied to DGA data analysis. The experimental data shows that, the proposed algorithm converges quickly, clusters samples effectively and recognizes faults properly.

引用

页码：15 / 18

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