基于加权模糊聚类算法的变压器故障诊断方法  

Transformer Fault Diagnosis Based on Weighted Fuzzy Clustering Algorithm

作　　者：杜正聪[1] 牛高远[2] 

机构地区：[1]攀枝花学院电气信息工程学院,四川攀枝花617000 [2]西华大学电气信息学院,成都610039

出　　处：《高压电器》2014年第4期42-48,共7页High Voltage Apparatus

基　　金：四川省青年科技基金项目(2010JQ0041);四川省应用基础研究项目(2011JY0115)~~

摘　　要：三比值法在变压器故障诊断中得到了广泛的应用,但是此方法存在编码不连续的问题,同时注意到不同样本在模糊C均值(fuzzy C-means,FCM)算法中所起到的作用差异,根据样本间相异度的思想,为每个样本赋予相应的权值,体现它们对聚类结果的不同影响,将加权FCM聚类算法应用到三比值法中进行变压器故障诊断,另外在聚类的开始,考虑到变压器故障诊断的实际情况,对算法的初始化隶属度也进行了更适当的设置。实验结果表明,经过以上修改得到的基于加权模糊聚类算法的变压器故障诊断方法有效可行,和FCM算法相比,不但能明显提高故障诊断的收敛速度,而且能得到更加接近实际位置的故障聚类中心,具有一定的优越性。The three-ratio method has been used widely in fault diagnosis of transformer, however its codes are discontinuous. Noting different sample has different effect in the fuzzy C-means （FCM）clustering algorithm, each sample is endowed with a suitable weight to reflect its impact on clustering results. We apply the weighted FCM clustering algorithm to the three-ratio method to diagnose transformer fault. Moreover, at the beginning of clustering, we set a more appropriate initial membership matrix to accord with the actual situation of transformer fault diagnosis. Experimental results show that the diagnosis method of transformer fault based on the weighted FCM clustering algorithm is effective and feasible, and it achieves faster convergence speed and the fault cluster center closer to the actual one, compared with the diagnosis method based on FCM clustering algorithm.

关 键 词：变压器 故障诊断 三比值法 加权FCM算法 收敛速度 

分 类 号：TM407[电气工程—电器]