A New Neural Network for Fault Diagnosis of Partial Discharge in Power Transformers

WANG Ru; LIN Hui

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A New Neural Network for Fault Diagnosis of Partial Discharge in Power Transformers

更新时间：2025-04-26

- A New Neural Network for Fault Diagnosis of Partial Discharge in Power Transformers
- High VoltageApparatus Issue 1, Pages: 36-38(2005)
- 作者机构：
  
  1. 西北工业大学自动化学院
  2. 西北工业大学自动化学院陕西西安710072
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM411
- Published：2005
- 稿件说明：
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[1]王茹,林辉.用RBF网络进行电力变压器局部放电故障诊断[J].高压电器,2005(01):36-38.

WANG Ru, LIN Hui. A New Neural Network for Fault Diagnosis of Partial Discharge in Power Transformers[J]. High voltageapparatus, 2005, (1): 36-38.
[1]王茹,林辉.用RBF网络进行电力变压器局部放电故障诊断[J].高压电器,2005(01):36-38. DOI：

WANG Ru, LIN Hui. A New Neural Network for Fault Diagnosis of Partial Discharge in Power Transformers[J]. High voltageapparatus, 2005, (1): 36-38. DOI：

摘要

用径向基函数（RBF）神经网络对变压器局部放电的6种放电类型进行了模式识别。研究结果表明

无论是放电的二维谱图还是三维谱图

RBF网络的学习收敛速度、识别率较BP网络都有很大的提高

同时避免了BP网络对初始权值敏感、陷入局部极小等问题

可作为电力变压器局部放电故障诊断的一种新型模式分类器。

Abstract

A new classification for fault diagnosis has been put forward

using RBF neural network to recognize 6 basic types of PD defects appearing in power transformers. Compared with BP-NN

the processing shows that the performance of NN is improved obviously

such as the convergence speed and discriminability. It also avoids the entrapment into local minimum problem and sensitivity problem to the initial value of BP-NN.

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The Method of Eliminating White Noise at On - line detection of Partial Discharge by Wavelet Analysis

Test Equipment of UHV Transformer’s AC Withstand Voltage and Partial Discharge Tests

Study on Fault Diagnosis for Power Transformer Based on Cloud Matter Element Analysis Principle and DGA

Transformer Multi-parameter Integrated Fault Diagnosis Method Based on Fuzzy Membership Function

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