The Research on the Method of Condition Estimate of Power Transformer Base on Support Vector Machine

摘要：

The transformer condition estimate model is constructed based on SVM and the parameter for SVM-based classifier is determined by adopting cross validation method. Considering the compactness characteristics of DGA data and combining the own characteristics of SVM,a method of fuzzy C-means clustering to pre-select representative samples is presented. Simulation results show that,the pre-selection of representative samples could solve the problem of time consuming on parameter determination and enable to detect transformer faults with higher diagnosis accuracy. The combination of fuzzy clustering method with SVM is also helpful to other pattern recognition problems.

关键词： power transformer condition estimate support vector machine pattern recognition

作者: Zhang Weizheng Yang Lanjun Du limin

作者单位: ZhengZhou Power Supply Company,No 9,Huaihe Road,Zhengzhou,450000,China Xian Jiaotong University,Xian,Shannxi,710040,China

会议类型: 国际会议

会议名称: 2010年中国国际供电会议(CICED 2010)

会议地点: 南京

会议语种:英文

页码: 753-756

在线出版日期: 2010-09-13（万方平台首次上网日期，不代表论文的发表时间）