计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (34): 233-235.DOI: 10.3778/j.issn.1002-8331.2009.34.073

• 工程与应用 • 上一篇    下一篇

一种变压器故障诊断新方法

赵文清,陈艺鑫,王晓辉   

  1. 华北电力大学 计算机科学与技术学院,河北 保定 071003
  • 收稿日期:2009-06-30 修回日期:2009-08-31 出版日期:2009-12-01 发布日期:2009-12-01
  • 通讯作者: 赵文清

Novel method for transformer faults diagnosis

ZHAO Wen-qing,CHEN Yi-xin,WANG Xiao-hui   

  1. School of Computer Science and Technology,North China Electric Power University,Baoding,Hebei 071003,China
  • Received:2009-06-30 Revised:2009-08-31 Online:2009-12-01 Published:2009-12-01
  • Contact: ZHAO Wen-qing

摘要: 提出一个基于欧氏聚类(Euclidean Clustering,EC)和支持向量机(Support Vector Machine,SVM)的变压器故障诊断模型及其求解步骤。选择典型油中气体作为模型的输入参数,按照变压器常见的13种故障类型,利用训练集样本数据建立基于EC和SVM多分类的组合故障诊断模型。通过与其他组合诊断的方法进行比较证明了该模型的有效性。

Abstract: A model and relative solving steps for power transformer fault diagnosis are proposed on the basis of Euclidean Clustering(EC) and Support Vector Machine(SVM) theory in this paper.Some key dissolved gases are selected as the inputs of the diagnosis model and data preprocessing is applied for these gases.According to thirteen fault types,a new model based on EC diagnosis model and SVM models is constructed.By comparing with the other methods,the proposed model reduces the error ratio,and recognition results show that this model is effective.

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