VMD引导的轮对与轴承复合故障诊断方法  

Compound Fault Diagnosis Method Guided by Variational Mode Decomposition for Wheelsets and Bearings

作　　者：易彩 林建辉[1] 汪浩[1] 廖小康 吴文逸 冉乐 YI Cai;LIN Jianhui;WANG Hao;LIAO Xiaokang;WU Wenyi;RAN Le(State Key Laboratory of Rail Transit Vehicle System,Southwest Jiaotong University,Chengdu 610031,China;School of Electrical Engineering,Southwest Jiaotong University,Chengdu 610031,China)

机构地区：[1]西南交通大学轨道交通运载系统全国重点实验室,四川成都610031 [2]西南交通大学电气工程学院,四川成都610031

出　　处：《西南交通大学学报》2024年第1期151-159,共9页Journal of Southwest Jiaotong University

基　　金：国家自然科学基金(51905453);中国博士后科学基金(2019M663899XB);西南交通大学牵引动力国家重点实验室自主课题(2020TPL-T14)对本文试验的资助.

摘　　要：针对列车轮对轴承系统复合故障难以辨识与诊断问题,提出一种变分模态分解(variational mode decomposition,VMD)引导的多故障特征提取匹配方法.首先,为避免预定义模式数在运行过程中对先验知识依赖从而对诊断结果造成影响,对原始轴箱振动数据进行逐阶VMD分解,模式数为2~N;其次,对VMD分解获取的本征模态函数(VMD intrinsic mode functions,VIMF)进行相关峭度计算,提取相关峭度最大的VIMF;然后,将相关峭度最大的VIMF进行平方包络分析,提取故障特征频率;最后,将所提方法与快速峭度谱、相关峭度谱方法进行对比.仿真信号和试验数据分析表明:所提方法完全规避了VMD模型中关键参数K的选择问题,可以准确、有效地分别提取出轮对和轴承的故障特征;与快速谱峭度与相关谱峭度方法相比,获取的故障特征谐波分量在数量和信噪比上均具有明显优势.A multi-fault feature extraction and matching method guided by variational mode decomposition(VMD)was proposed to address the difficulty in identifying and diagnosing composite faults in train wheelset bearing systems.Firstly,in order to avoid the pre-defined mode number relying on prior knowledge during operation and thus affecting the diagnosis results,the original axle-box vibration data are directly decomposed by VMD step by step,and the number of modes is 2–N.Secondly,the VMD intrinsic mode functions(VIMF)obtained by VMD are calculated to extract the VIMF with the largest correlation kurtosis;then,the determined VIMF is analyzed by square envelope analysis to extract the fault feature frequency.Finally,the proposed method is compared with the fast spectral Kurtogram method and the correlation Kurtogram method.The analysis of simulation signals and experimental data shows that the proposed method can completely avoids the problem of selecting the key parameter K in the VMD model,and can accurately and effectively extract the fault characteristics of wheelsets and bearings,respectively.Compared with the fast spectral Kurtogram method and the correlation Kurtogram method the proposed method can diagnose compound faults effectively,and the obtained fault feature harmonic components are more advantageous in quantity and signal-to-noise ratio.

关 键 词：变分模态分解 复合故障诊断 轮对轴承 相关峭度 平方包络 

分 类 号：U279.323[机械工程—车辆工程]