Fault Diagnosis Model of DGA for Power Transformer Based on Kernel Fisher Discriminant Analysis Technology

WU Xiao-hui1; WANG Song1; FANG Xiao-ming1; LI Yan-mu2; LI Yan-ming1

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Fault Diagnosis Model of DGA for Power Transformer Based on Kernel Fisher Discriminant Analysis Technology

更新时间：2025-04-26

- Fault Diagnosis Model of DGA for Power Transformer Based on Kernel Fisher Discriminant Analysis Technology
- High VoltageApparatus Issue 3, Pages: 214-217(2007)
- 作者机构：
  
  1. 西安交通大学电气工程学院
  2. 西安建筑科技大学机电学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM41;TM743
- Published：2007
- 稿件说明：
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[1]吴晓辉,王颂,方晓明,李延沐,李彦明.基于核Fisher判别分析技术的电力变压器DGA故障诊断模型研究[J].高压电器,2007(03):214-217.

WU Xiao-hui1, WANG Song1, FANG Xiao-ming1, et al. Fault Diagnosis Model of DGA for Power Transformer Based on Kernel Fisher Discriminant Analysis Technology[J]. High voltageapparatus, 2007, (3): 214-217.
[1]吴晓辉,王颂,方晓明,李延沐,李彦明.基于核Fisher判别分析技术的电力变压器DGA故障诊断模型研究[J].高压电器,2007(03):214-217. DOI：

WU Xiao-hui1, WANG Song1, FANG Xiao-ming1, et al. Fault Diagnosis Model of DGA for Power Transformer Based on Kernel Fisher Discriminant Analysis Technology[J]. High voltageapparatus, 2007, (3): 214-217. DOI：

摘要

鉴于核Fisher判别分析技术（KFDA）在模式识别问题中表现出的良好性能

提出了基于KFDA的变压器故障诊断模型

该模型首先提出了区分放电及过热两大类故障的特征量

并用KFDA分类器来识别类内故障的具体类别。采用基于网格搜索的交叉验证法来选择模型参数

避免了参数选择的盲目性和随意性。实例分析表明

该模型具有训练时间短、不存在局部极小等优点

与IEC三比值及改良电协研法相比

具有更好的故障识别效果。

Abstract

In view of the good performance in pattern recognition using Kernel Fisher Discriminant Analysis（KFDA） method

this paper presented a fault diagnosis model of power transformer based on KFDA.The model extracted a feature to distinguish between discharge faults and hot faults first

and then used the KFDA classifier to distinguish in discharge faults or hot faults.To choose parameters of the model

this paper adopted the method of cross validation based on grid search

avoiding the arbitrary and capricious behavior.Practical analysis indicates that this model has advantages of short training time and no part teeny problem.Compared with three rations method of IEC and the improved three rations method

this model has considerable effectiveness of faults identification.

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Related Author

WANG Xiao-ming1

HE Ping1

WU Hua1

CHEN Zhen-gang1

OU YANG Jin2

LI Yan-ming3

HUANG Xinbo

LI Wenjunzi

Related Institution

Ultra High Voltage Transmission Subcompany of Jiangxi Electric Power Corporation

Jiangxi Nanchang Power Corporation

College of Electronics and Information,Xi’an Polytechnic University

China Nuclear Power Engineering Co., Ltd.

School of Electrical Engineering, Hebei University of Science and Technology

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