Study on Fault Diagnosis of High Voltage Circirt Breaker Based on Spectral Kurtosis Analysis and Particle Swarm Optimization Kmeans Clustering Algorithm

WANG Qingyan; CAO Shengrang; CHEN Bingyan; YANG Zhong

doi:10.13296/j.1001-1609.hva.2019.05.004

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Study on Fault Diagnosis of High Voltage Circirt Breaker Based on Spectral Kurtosis Analysis and Particle Swarm Optimization Kmeans Clustering Algorithm

更新时间：2025-04-26

- Study on Fault Diagnosis of High Voltage Circirt Breaker Based on Spectral Kurtosis Analysis and Particle Swarm Optimization Kmeans Clustering Algorithm
- High VoltageApparatus Vol. 55, Issue 5, Pages: 23-28+34(2019)
- 作者机构：
  
  1. 金陵科技学院机电学院
  2. 南京航空航天大学自动化学院
  3. 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.2019.05.004
  CLC： TM561
- Published：2019
- 稿件说明：
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[1]王庆燕,曹生让,陈秉岩,杨忠.基于谱峭度分析和粒子群Kmeans算法的高压断路器故障诊断研究[J].高压电器,2019,55(05):23-28+34.

WANG Qingyan, CAO Shengrang, CHEN Bingyan, et al. Study on Fault Diagnosis of High Voltage Circirt Breaker Based on Spectral Kurtosis Analysis and Particle Swarm Optimization Kmeans Clustering Algorithm[J]. High voltageapparatus, 2019, 55(5): 23-28+34.
[1]王庆燕,曹生让,陈秉岩,杨忠.基于谱峭度分析和粒子群Kmeans算法的高压断路器故障诊断研究[J].高压电器,2019,55(05):23-28+34. DOI： 10.13296/j.1001-1609.hva.2019.05.004.

WANG Qingyan, CAO Shengrang, CHEN Bingyan, et al. Study on Fault Diagnosis of High Voltage Circirt Breaker Based on Spectral Kurtosis Analysis and Particle Swarm Optimization Kmeans Clustering Algorithm[J]. High voltageapparatus, 2019, 55(5): 23-28+34. DOI： 10.13296/j.1001-1609.hva.2019.05.004.

摘要

为满足电网对高压断路器高效诊断要求

提出一种谱峭度分析和粒子群K均值算法（PSO-Kmeans）相结合的故障诊断方法。该方法首先对正常状态和故障状态振动信号进行快速Kurtogram谱峭度分析

得到谱峭度指标最大中心频率和相应频率分辨率

据此设计带通滤波器对信号进行去噪;对去噪后的信号进行小波分解

提取小波包能量熵作为特征量;进一步采用PSO-Kmeans对特征量进行聚类分析。实验结果表明:改进谱峭度分析法弥补了传统带通滤波器参数确定的不足

提升去噪效果;去噪与PSO-Kmeans算法相结合的诊断方法克服了传统Kmeans易受初始聚类中心影响的缺点

聚类效果良好且精度高于传统算法

证实该方法适用于高精度高压断路器机械故障诊断。

Abstract

In order to meet the power grid requirement of high precision circuit breaker fault diagnosis

an improved spectral kurtosis analysis combined with PSO Kmeans algorithm is proposed. Firstly

the Kurtogram spectrum analysis is performed for normal and fault vibration signals

the central and the corresponding frequencies are obtained

the band pass filter is designed;The de-noising signal is decomposed by wavelet

the wavelet packet energy entropy is extracted;PSO-Kmeans is used to cluster the feature quantity. It is proved that

the effectiveness of designed filter is verified;The employed PSO-Kmeans algorithm overcomes the shortcoming of traditional Kmeans

achieves good clustering results and improves the accuracy of fault diagnosis. The method is suitable for high-precision mechanical fault diagnosis of high voltage circuit breaker.

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