基于参数优化变分模态分解的交流继电器交流声故障特征提取  

Hum Fault Feature Extraction of AC Relay Based on Parameter Optimization VMD

作　　者：谢鸿凯 鲍光海[1] XIE Hongkai;BAO Guanghai(College of Electrical Engineering and Automation,Fuzhou University,Fuzhou 350108,China)

机构地区：[1]福州大学电气工程与自动化学院,福州350108

出　　处：《电器与能效管理技术》2022年第6期51-56,63,共7页Electrical & Energy Management Technology

摘　　要：针对大背景噪声下交流继电器的交流声故障特征提取效果不佳的问题,提出了一种基于参数优化变分模态分解(VMD)的故障特征提取方法。首先,采用樽海鞘群算法(SSA)对VMD的参数进行寻优,利用得到的最优值对故障信号进行VMD分解,得到若干本征模态函数(IMF),然后根据峭度准则筛选分解后的IMF分量,选择峭度最大的IMF分量作为有效分量,进行Hilbert包络解调分析,提取交流声故障特征。最后,仿真信号和实验数据的分析结果表明,相比于经验模态分解(EMD)方法,所提方法提取交流继电器的交流声故障特征可行且效果更佳,具有较高的应用价值。Aiming at the problem of poor performance of AC relay hum fault feature extraction under large background noise,a fault feature extraction method based on the parameter optimization variational modal decomposition(VMD)is proposed.First,the salp swarm algorithm is used to optimize the parameters of VMD,and the obtained optimal value is used to perform VMD decomposition of the fault signal to obtain a number of intrinsic mode functions(IMF).Then the decomposed IMF components is filtered according to the kurtosis criterion,the IMF component with the largest kurtosis is selected as the effective component,and the Hilbert envelope demodulation analysis is performed to extract the feature of the hum fault.Finally,the analysis results of the simulation signals and experimental datas show that the proposed method is feasible and effective in extracting the hum fault characteristics of AC relays and has higher application value compared to the empirical mode decomposition(EMD)method.

关 键 词：故障特征提取 交流声 变分模态分解 樽海鞘群算法 峭度准则 

分 类 号：TM58[电气工程—电器]