基于改进变分模态分解和SVM的断路器机械故障振动分析

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振动与冲击 ›› 2019, Vol. 38 ›› Issue (23) : 90-95.

论文

田书，康智慧

作者信息 +

Circuit breaker mechanical fault vibration analysis based on improved variational mode decomposition and SVM

TIAN Shu, KANG Zhihui

Author information +

文章历史 +

摘要

针对传统信号分解导致断路器机械故障振动分析特征提取不准确，故障诊断精度低的缺点，提出将改进变分模态分解能量熵与支持向量机相结合的断路器故障诊断新方法。利用量子粒子群优化变分模态分解(VMD)参数设置问题，获取最佳模态个数及惩罚因子。为验证该算法在模态混叠及噪声干扰方面的优势，将其应用在10 kV高压断路器ZN63A-12上，对断路器采集到的正常、传动机构卡涩及基座螺丝松动三种振动信号进行分析。用改进VMD能量熵提取断路器振动特征，并输入支持向量机确定故障状态。实验结果表明，所提方法在少量样本情况下仍能有效提取断路器的运行状态并对故障进行分类，具有较高的应用价值。

Abstract

Aiming at shortcomings of traditional signal decomposition causing circuit breaker’s incorrect mechanical fault vibration analysis feature extraction and lower fault diagnosis accuracy, a new method for circuit breaker fault diagnosis based on the improved variational mode decomposition (VMD) energy entropy combined with support vector machine (SVM) was proposed.The setting of VMD parameters was optimized by using the quantum-behaved particle swarm optimization (QPSO) method to obtain the optimal mode number and penalty factor.In order to verify this method’s advantages in suppressing mode aliasing and noise interference, it was applied to analyze a 10 kV high voltage circuit breaker 10kV high voltage circuit breaker ZN63A-12’s three kinds of vibration signals collected in cases of normal, transmission mechanism jamming and base screw loosing.The improved VMD energy entropy was used to extract vibration features of the circuit breaker ZN63A-12, and these features were input into a support vector machine to determine ZN63A-12’s fault state.Test results showed that the proposed method can be used to effectively extract fault vibration features of the circuit breaker, and classify faults under the condition of a few samples, so it has higher application value.
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导出引用

田书，康智慧. 基于改进变分模态分解和SVM的断路器机械故障振动分析[J]. 振动与冲击, 2019, 38(23): 90-95

TIAN Shu, KANG Zhihui. Circuit breaker mechanical fault vibration analysis based on improved variational mode decomposition and SVM[J]. Journal of Vibration and Shock, 2019, 38(23): 90-95

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