Mechanical Fault Diagnosis Method of High Voltage Circuit Breaker Based on LVQ Neural Network

MA Hongzhong; XU Yan; WEI Haizeng; LIU Yongye

doi:10.13296/j.1001-1609.hva.2019.08.005

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Mechanical Fault Diagnosis Method of High Voltage Circuit Breaker Based on LVQ Neural Network

更新时间：2025-04-26

- Mechanical Fault Diagnosis Method of High Voltage Circuit Breaker Based on LVQ Neural Network
- High VoltageApparatus Vol. 55, Issue 8, Pages: 30-36(2019)
- 作者机构：
  
  河海大学能源与电气学院
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2019.08.005
  CLC： TM561
- Published：2019
- 稿件说明：
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[1]马宏忠,徐艳,魏海增,刘勇业.基于LVQ神经网络的高压断路器机械故障诊断方法[J].高压电器,2019,55(08):30-36.

MA Hongzhong, XU Yan, WEI Haizeng, et al. Mechanical Fault Diagnosis Method of High Voltage Circuit Breaker Based on LVQ Neural Network[J]. High voltageapparatus, 2019, 55(8): 30-36.
[1]马宏忠,徐艳,魏海增,刘勇业.基于LVQ神经网络的高压断路器机械故障诊断方法[J].高压电器,2019,55(08):30-36. DOI： 10.13296/j.1001-1609.hva.2019.08.005.

MA Hongzhong, XU Yan, WEI Haizeng, et al. Mechanical Fault Diagnosis Method of High Voltage Circuit Breaker Based on LVQ Neural Network[J]. High voltageapparatus, 2019, 55(8): 30-36. DOI： 10.13296/j.1001-1609.hva.2019.08.005.

摘要

高压断路器作为电力系统的开关及保护设备

其可靠地工作对整个电力系统的安全运行具有很大的意义。为了迅速、精确地诊断高压断路器故障

提出一种基于学习向量量化（LVQ）网络的高压断路器机械故障诊断方法。首先

模拟高压断路器灭弧室机械故障状态

采集断路器的机械振动信号;其次

提取高压断路器机械故障振动信号的小波包能量作为特征量

建立基于LVQ网络的高压断路器机械故障诊断模型;最后

将LVQ网络、思维进化优化（MEA）的LVQ网络、BP网络和RBF网络在网络迭代步数、网络误差以及预测置信度方面进行比较。结果表明

提出的基于LVQ神经网络的高压断路器机械故障诊断方法相比较于其他诊断方法具有一定的快速性

并具有较高的置信度。

Abstract

High voltage circuit breaker as power system switching and protection equipment

reliable working on the entire power system safe operation is of great significance.In order to diagnose the fault type of high voltage circuit breaker quickly and accurately

a mechanical fault diagnosis method of high voltage circuit breaker based on learning vector quantization（LVQ）network is proposed.Firstly

the mechanical vibration signal of the circuit breaker is simulated and the mechanical vibration signal of the circuit breaker is collected.Secondly

the wavelet packet energy of the mechanical fault vibration signal of high voltage circuit breaker is extracted as the feature quantity which to establish the mechanical fault diagnosis model of high voltage circuit breaker based on LVQ network.Finally

the LVQ network

the LVQ network of thought evolutionary optimization（MEA）

the RBF network are compared in terms of the number of iteration of the network

the network error

and the confidence in the prediction.The results show that the mechanical fault diagnosis method of high voltage circuit breaker based on LVQ neural network is faster than other diagnostic methods and has high confidence.

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