变压器故障诊断中溶解气体的PSO-WFCM算法研究  

Detection of Dissolved Gas with PSO-WFCM Algorithm for Fault Diagnosis of Power Transforme

作　　者：马叶芝[1] 焦彦军[1] 王东升[1] 吕佳[1] 马威[2] 

机构地区：[1]华北电力大学(保定),河北保定071003 [2]河北能源工程设计有限公司,石家庄050000

出　　处：《高压电器》2014年第1期72-76,共5页High Voltage Apparatus

摘　　要：由于模糊聚类将故障样本等同进行模糊划分,且受初始值影响,故提出将PSO-WFCM算法用于变压器油中溶解气体的故障诊断。该算法选取油中气体作为故障特征量,利用粒子群算法得到最佳初始聚类中心,用以指导模糊聚类求取最终的聚类中心。实验结果表明,其弥补了模糊聚类的不足,还提高了变压器的诊断性能。Because the samples are divided equally and the division is sensitive to the initial value in fuzzy clustering method, this paper applies PSO-WFCM algorithm to detection of dissolved gas for fault diagnosis of power transformer. In PSO-WFCM algorithm, the dissolved gas in oil is taken as the characteristic quantity of fault, and PSO is adopted to obtain the optimal initial cluster centers for achieving the final cluster centers via fuzzy clustering. Experiments show that the proposed method makes up for the deficiency of fuzzy clustering method, and improves fault diagnosis for transformer.

关 键 词：PSO—WFCM 变压器 油中溶解气体 故障诊断 

分 类 号：TM41[电气工程—电器]