基于多元变分模态分解和1.5维谱的滚动轴承故障诊断  

Fault Diagnosis for Rolling Bearing Based on Multivariate Variational Modal Decomposition and 1.5-Dimensional Spectrum

作　　者：唐贵基[1] 薛贵 王晓龙[1] 丁傲 TANG Guiji;XUE Gui;WANG Xiaolong;DING Ao(Department of Mechanical Engineering,North China Electric Power University,Baoding 071003,China)

机构地区：[1]华北电力大学机械工程系,河北保定071003

出　　处：《轴承》2022年第12期74-82,共9页Bearing

基　　金：国家自然科学基金资助项目(52005180);河北省自然科学基金资助项目(E2020502031,E2022502003);河北省高等学校科学技术研究资助项目(QN2022190);中央高校基本科研业务费专项资金资助项目(2021MS069)。

摘　　要：针对变分模态分解(VMD)仅适用于分析滚动轴承单信道信号,而对分析同一滚动轴承的多信道信号缺乏理论依据的局限性,提出了一种基于多元变分模态分解(MVMD)和1.5维谱的滚动轴承故障诊断方法。首先,提出了基于能量系数指标的参数寻优法,利用设定好最优参数的MVMD方法对滚动轴承多信道故障数据进行自适应分解;其次,从分解后的本征模态函数(IMF)中寻找最优分量并提取信号的时域特征,再对其进行包络解调运算;最后,计算包络信号的1.5维谱并分析谱中提取到的故障特征信息,对故障类型进行诊断。针对滚动轴承的故障诊断试验证明了该方法能够有效提取轴承微弱故障的特征信息,实现轴承故障特征的准确诊断。In view of the limitation that variational modal decomposition(VMD)is only suitable for analyzing the single-channel signals of rolling bearing,but there is no theoretical basis for analyzing the multi-channel signals of same rolling bearing,a fault diagnosis method is proposed for rolling bearing based on multivariate variational modal decomposition(MVMD)and 1.5-dimensional spectrum.Firstly,a parameter optimization method based on energy coefficient index is proposed,and the MVMD algorithm with optimal parameters is used to adaptively decompose the multi-channel fault data of rolling bearing;secondly,the optimal component is found from decomposed intrinsic mode function(IMF)and the time-domain characteristics of the signal are extracted,and then the envelope demodulation operation is performed;finally,the 1.5-dimensional spectrum of envelope signal is calculated and the fault characteristic information extracted from spectrum is analyzed to diagnose the fault types.The fault diagnosis experiment of rolling bearing shows that this method is able to extract the characteristic information of weak fault of the bearing effectively and realize the accurate diagnosis of fault characteristics of the bearing.

关 键 词：滚动轴承 故障诊断 时域 频谱 谱包络 信号重构 

分 类 号：TH133.33[机械工程—机械制造及自动化] TN911.7[电子电信—通信与信息系统]