Power Transformer Fault Diagnosis Based on Immune Evolutionary Clustering Algorithm

摘要：

In this paper, Fuzzy C-Means (FCM) algorithm is combined with the immune evolutionary algorithm to propose a new method which can be applied to transformer fault diagnosis. First, the paper makes attributes reduction in decision table with the use of rough set, then the continuous attributes in the decision table use immune evolutionary clustering algorithm for discrete processing, and then builds transformer fault diagnosis system. Experiments show that the transformer fault diagnosis system has the feasibility and high accuracy.

关键词： rough set Fuzzy Cluster Immune Evolutionary Fault Diagnosis

作者: Xie Hong-xia Shi Li-ping

作者单位: School of Information and Electrical Engineering,China University of Mining and Technology Xuzhou, C School of Information and Electrical Engineering,China University of Mining and Technology Xuzhou, C

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)

会议地点: 大连

会议语种:英文

页码: 881-885

在线出版日期: 2010-07-05（万方平台首次上网日期，不代表论文的发表时间）