基于AMCKD和改进谱分割经验小波变换的滚动轴承微弱故障诊断  

Diagnosis on Weak Fault of Rolling Bearings Based on AMCKD andImproved Spectral Segmentation Empirical Wavelet Transform

作　　者：马永杰[1] 杨彩红[1] 何文 MA Yongjie;YANG Caihong;HE Wen(College of Mechanical and Electrical Engineering,Henan Vocational College of Agriculture,Zhengzhou 451450,China;College of Mechanical and Vehicle Engineering,Taiyuan University of Technology,Taiyuan 030024,China)

机构地区：[1]河南农业职业学院机电工程学院,郑州451450 [2]太原理工大学机械与运载工程学院,太原030024

出　　处：《轴承》2023年第8期73-78,86,共7页Bearing

基　　金：国家自然科学基金资助项目(51905367);河南农业职业学院机械工程智能化科研创新团队基金资助项目(HNACKT-2020-04)。

摘　　要：针对滚动轴承振动信号传递路径长、强噪声环境下故障特征微弱的问题,提出一种基于自适应最大相关峭度解卷积(AMCKD)和改进谱分割经验小波变换(ISSEWT)的滚动轴承微弱故障检测方法。首先,基于功率谱熵评价准则进行最大相关峭度解卷积滤波器阶数和解卷积周期的自适应选取,采用变步长参数搜索方法进行参数寻优并通过AMCKD对信号进行初次降噪;然后,采用ISSEWT对信号频谱进行有效边界划分从而将信号自动分解为不同频段的分量,利用峭度指标对主要分量进行重构完成二次降噪;最后,对降噪后信号进行包络谱分析,实现滚动轴承微弱故障故障检测。试验结果表明,相对于POMCKD,CASNEWT,ABSEWT,CASNEWT等方法,AMCKD-ISSEWT对滚动轴承故障特征的提取效果更明显,适用于轴承微弱故障的诊断。Aimed at the problems of long transmission paths of vibration signal and weak fault characteristics of rolling bearings under strong noise environment,a detection method for weak fault of the bearings is proposed based on adaptation maximum correlated kurtosis deconvolution(AMCKD)and improved spectral segmentation empirical wavelet transform(ISSEWT).Firstly,based on power spectrum entropy evaluation criterion,the maximum correlation kurtosis deconvolution filter order and deconvolution period are adaptively selected.The variable step parameter search method is used for parameter optimization,and the signal is firstly denoised by AMCKD.Then,ISSEWT is used to divide the effective boundary of signal spectrum,so that the signal is automatically decomposed into components of different frequency bands,and then the main components are reconstructed by using kurtosis index for secondary denoising.Finally,the envelope spectrum analysis of denoised signal is carried out to realize the detection for weak fault of the bearings.The test results show that AMCKD-ISSEWT is more effective than POMCKD,CASNEWT,ABSEWT and CASNEWT in fault feature extraction of the bearings,suiting for diagnosis on weak fault of the bearings.

关 键 词：滚动轴承 故障诊断 经验小波变换 最大相关峭度解卷积 峭度 

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]