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基于支持向量机和DGA的变压器状态评估方法
引用本文:申涛,朱永利,李强,苏蓬.基于支持向量机和DGA的变压器状态评估方法[J].电力科学与工程,2008,24(2):47-50.
作者姓名:申涛  朱永利  李强  苏蓬
作者单位:华北电力大学,电气与电子工程学院,河北,保定,071003
摘    要:针对电力变压器结构、老化、故障机理复杂,具有不确定性,难以进行准确的状态评估的问题,将变压器健康状态分为良好、一般、注意、较差4种状态,提出了一种基于支持向量机的二叉树多级分类器变压器健康状态评估方法。该模型以变压器油中溶解气体的产气量和产气速率为评价指标,利用支持向量机挖掘评价指标与变压器健康状况之间的关系。

关 键 词:变压器  支持向量机  油中溶解气体分析  状态评估
修稿时间:2007年10月19

Power Transformer Condition Evaluation Based on Support Vector Machine and DGA
Shen Tao,Zhu Yongli,Li Qiang,Su Peng.Power Transformer Condition Evaluation Based on Support Vector Machine and DGA[J].Power Science and Engineering,2008,24(2):47-50.
Authors:Shen Tao  Zhu Yongli  Li Qiang  Su Peng
Abstract:Aiming at the problem that power transformer structure,ageing,fault mechanism are complex and their conditions are difficult to evaluate accurately,a condition assessment method that synthetically considering the transformer dissolved gas analysis(DGA) technique based on support vector machine is proposed in this paper.The transformer condition is divided into four grades: "fine","general","pay attention to","relatively poor",using support vector machine and binary tree to decide its condition.
Keywords:power transformer  support vector machine(SVM  ) dissolved gas analysis(DGA)  condition evaluation
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