Research on Mechanical Fault Diagnosis of High Voltage Circuit Breaker Based on EEMD and Mahalanobis Distance Discriminant

SUN Kang; LIU Yongchao

doi:10.13296/j.1001-1609.hva.2018.12.007

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Research on Mechanical Fault Diagnosis of High Voltage Circuit Breaker Based on EEMD and Mahalanobis Distance Discriminant

更新时间：2025-04-26

- Research on Mechanical Fault Diagnosis of High Voltage Circuit Breaker Based on EEMD and Mahalanobis Distance Discriminant
- High VoltageApparatus Vol. 54, Issue 12, Pages: 43-49(2018)
- 作者机构：
  
  河南理工大学
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2018.12.007
  CLC： TM561
- Published：2018
- 稿件说明：
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[1]孙抗,刘永超.基于EEMD和马氏距离的高压断路器机械故障诊断研究[J].高压电器,2018,54(12):43-49.

SUN Kang, LIU Yongchao. Research on Mechanical Fault Diagnosis of High Voltage Circuit Breaker Based on EEMD and Mahalanobis Distance Discriminant[J]. High voltageapparatus, 2018, 54(12): 43-49.
[1]孙抗,刘永超.基于EEMD和马氏距离的高压断路器机械故障诊断研究[J].高压电器,2018,54(12):43-49. DOI： 10.13296/j.1001-1609.hva.2018.12.007.

SUN Kang, LIU Yongchao. Research on Mechanical Fault Diagnosis of High Voltage Circuit Breaker Based on EEMD and Mahalanobis Distance Discriminant[J]. High voltageapparatus, 2018, 54(12): 43-49. DOI： 10.13296/j.1001-1609.hva.2018.12.007.

摘要

断路器的振动信号可以有效反映其机械运行状态

针对目前使用振动信号判别断路器常见机械故障正确率较低的现状

提出一种基于集合经验模态分解（EEMD）和马氏距离判别法的高压断路器机械故障诊断方法。首先

针对断路器振动信号的瞬时非平稳特性

使用EEMD将其分解得到若干个固有模态函数（IMF）。然后

基于EEMD的能量熵并联合其均方根值

构造一种新的故障特征向量。最后

利用马氏距离判别法进行机械故障识别。实验结果表明

该方法用于识别断路器正常、传动机构卡涩和基座螺丝松动等常见机械故障时

正确率可达到95.7%

具有较高的实际应用价值。

Abstract

The vibration signal of the circuit breaker can reflect the mechanical state of the circuit breaker effectively.Aiming at the present situation of low accuracy by using the vibration signal to judge the common mechanical failure of the circuit breaker

a new method based on the combination of empirical mode decomposition（EEMD）and Mahalanobis distance Mechanical Fault Diagnosis Method for high voltage circuit breaker is proposed.First

the instantaneous non-stationary characteristics of the vibration signal of the circuit breaker are decomposed into several intrinsic mode functions（IMF）using EEMD.Then

based on the energy entropy of EEMD and its root mean square value

a new fault feature vector is constructed.Finally

the Mahalanobis distance discriminant method is used to identify the mechanical faults.The experimental results show that the method can be used to identify the common mechanical faults such as the normal circuit breaker

the transmission mechanism jammed and the loosening of the base screw.The correct rate can reach 95.7%

which has high practical application value.

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Related Institution

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