Research on Typical Artificial Neural Networks in Power Transformer Fault Diagnosis

HU Han-mei1; BAO Liang-liang1; ZHAO Hai-jun2

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Research on Typical Artificial Neural Networks in Power Transformer Fault Diagnosis

更新时间：2025-04-26

- Research on Typical Artificial Neural Networks in Power Transformer Fault Diagnosis
- High VoltageApparatus Issue 3, Pages: 217-220(2008)
- 作者机构：
  
  1. 三峡大学电气信息学院
  2. 晋城煤业集团长平公司
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM407;TP183
- Published：2008
- 稿件说明：
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[1]胡汉梅,鲍亮亮,赵海军.神经网络在变压器故障诊断中典型算法研究[J].高压电器,2008(03):217-220.

HU Han-mei1, BAO Liang-liang1, ZHAO Hai-jun2. Research on Typical Artificial Neural Networks in Power Transformer Fault Diagnosis[J]. High voltageapparatus, 2008, (3): 217-220.
[1]胡汉梅,鲍亮亮,赵海军.神经网络在变压器故障诊断中典型算法研究[J].高压电器,2008(03):217-220. DOI：

HU Han-mei1, BAO Liang-liang1, ZHAO Hai-jun2. Research on Typical Artificial Neural Networks in Power Transformer Fault Diagnosis[J]. High voltageapparatus, 2008, (3): 217-220. DOI：

摘要

为了随时检测变压器状态

及早发现并排除变压器可能存在的故障

笔者将3种不同的神经网络（即BP网络、GA-BP网络与RBF网络）应用于变压器故障诊断中

分别介绍了这3种网络的结构及原理

故障诊断采用MATLAB语言编程实现。大量实验数据结果分析表明

RBF网络在诊断准确率相比其他两种网络具有一定的优势。

Abstract

In order to examine transformer momentarily to exclude possible fault in time

three kinds of artificial neural network were applied in the transformer fault diagnosis

such as the BP network

the GA-BP network

and RBF network. The structures and principles of the three networks were analyzed

and fault diagnosis was realized by MATLAB programming. The analysis of the massive experimental data indicate that the RBF network is better than the others in diagnostic accuracy.

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