New Approach to Transformer Fault Diagnosis Based on ANN

doi:10.13296/j.1001-1609.hva.2000.06.003

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New Approach to Transformer Fault Diagnosis Based on ANN

更新时间：2025-04-26

- New Approach to Transformer Fault Diagnosis Based on ANN
- High VoltageApparatus Issue 6, Pages: 12-14+22(2000)
- 作者机构：
  
  1. 上海交通大学!上海200030
  2. 南方电力平果有限公司!平果531400
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2000.06.003
  CLC： TM406
- Published：2000
- 稿件说明：
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[1]李红雷,肖登明,赵杰,潘勇斌.神经网络诊断变压器故障的新方法[J].高压电器,2000(06):12-14+22.

New Approach to Transformer Fault Diagnosis Based on ANN[J]. High voltageapparatus, 2000, (6): 12-14+22.
[1]李红雷,肖登明,赵杰,潘勇斌.神经网络诊断变压器故障的新方法[J].高压电器,2000(06):12-14+22. DOI： 10.13296/j.1001-1609.hva.2000.06.003.

New Approach to Transformer Fault Diagnosis Based on ANN[J]. High voltageapparatus, 2000, (6): 12-14+22. DOI： 10.13296/j.1001-1609.hva.2000.06.003.

摘要

介绍了一种用于信号分类识别的小波神经网络，其网络权值由小波函数集充当，并在学习过程中应用了共轭梯度法。将此小波神经网络用于变压器油色谱诊断，经仿真计算，证实它具有比ＢＰ网络更好的逼近性能，可以达到较高的准确率。

Abstract

This paper describes a wavelet artifi- cial neural network（ANN）for signal classification

and applies it for transformer fault detection with dissolved gas analysis （DGA）.The weights of the network are replaced by wavelet hations and are corrected by conjugate gradient method in the training iteration. Preliminary simulation results show the wavelet ANN for DGA can get a good correct diagnosis rate superior to BP ANN.

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Related Institution

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