Application of Multiple Neural Networks Method in DGA Fault Diagnosis of Transformer Oil

XU Zhi-niu; LU Fang-cheng

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Application of Multiple Neural Networks Method in DGA Fault Diagnosis of Transformer Oil

更新时间：2025-04-26

- Application of Multiple Neural Networks Method in DGA Fault Diagnosis of Transformer Oil
- High VoltageApparatus Issue 3, Pages: 206-208(2005)
- 作者机构：
  
  1. 华北电力大学电力系统保护与动态安全监控教育部重点实验室
  2. 华北电力大学电力系统保护与动态安全监控教育部重点实验室河北保定071003
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM407
- Published：2005
- 稿件说明：
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[1]徐志钮,律方成.多神经网络方法在变压器油色谱故障诊断中的应用[J].高压电器,2005(03):206-208.

XU Zhi-niu, LU Fang-cheng. Application of Multiple Neural Networks Method in DGA Fault Diagnosis of Transformer Oil[J]. High voltageapparatus, 2005, (3): 206-208.
[1]徐志钮,律方成.多神经网络方法在变压器油色谱故障诊断中的应用[J].高压电器,2005(03):206-208. DOI：

XU Zhi-niu, LU Fang-cheng. Application of Multiple Neural Networks Method in DGA Fault Diagnosis of Transformer Oil[J]. High voltageapparatus, 2005, (3): 206-208. DOI：

摘要

电力变压器的故障诊断对于变压器的维护起着至关重要的作用

诊断的可信度能给变压器维护提供更好的依据。为了克服单个神经网络不能给出诊断结果可信度的缺点

将多神经网络方法引入到变压器油色谱故障诊断中

利用多个神经网络对变压器诊断结果的方差给出了诊断结果的可信度;同时将多个网络输出的平均作为网络的诊断结果

减少了网络诊断的误差

提高了诊断的准确率。故障变压器实例验证了多神经网络方法的有效性。

Abstract

Fault diagnosis is important to the maintenance work of power transformer. But the diagnosis should be reliable. Single ANN diagnosis method can not give an information of reliability. So

this paper uses multiple ANNs method to diagnose transformer fault based on dissolved gas-in-oil analysis（DGA）. The results as well as the reliability is provided. The effect of multiple ANNs method is verified by practical applications of cases.

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