基于STFD的轴承多故障信号欠定盲源分离方法  

Underdetermined Blind Source Separation Method for Multiple Fault Signals of Bearing Based on STFD

作　　者：诸葛航 吕勇[1] 易灿灿[1] 袁锐[1] ZHUGE Hang;LV Yong;YI Can-can;YUAN Rui(School of Machinery and Automation,Wuhan University of Science and Technology,Wuhan 430081,China)

机构地区：[1]武汉科技大学机械自动化学院,武汉430081

出　　处：《组合机床与自动化加工技术》2021年第11期62-67,共6页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国家自然科学基金项目(51875416);湖北省自然科学基金创新群体项目(2020CFA033)。

摘　　要：研究了一种基于空间-时频分布(STFD)的欠定盲源分离方法,并将其应用于滚动轴承的多故障振动信号的盲源分离与故障诊断。通过计算平滑伪Wigner-Ville分布(SPWVD)并将其扩展到三维空间,得到了观测信号的空间-时频分布(STFD)矩阵;再对STFD矩阵进行噪声阈值处理、自动项筛选、聚类操作后得到估计源信号的二次时频分布(QTFD);之后基于Wigner-Ville分布(WVD)的反演特性重建源信号。最后通过相关系数将估计源信号与观测信号对应来对故障进行定位。最后设计实验进行验证,仿真结果证明了方法的有效性。An underdetermined blind source separation(BSS)method based on spatial time-frequency distribution is studied and applied to blind source separation and fault diagnosis of multi fault vibration signals of rolling bearing.In this method,the smoothed pseudo Wigner-Ville distribution(SPWVD)is calculated and extended to three-dimensional space to obtain the spatial time-frequency distribution(STFD)matrix of the observed signals.After noise threshold processing,automatic term screening and clustering operations,the quadratic time-frequency distribution(QTFD)of the estimated source signal is obtained.Then,the source signal is reconstructed based on the inversion characteristics of Wigner-Ville distribution(WVD).Finally,the estimated source signal is corresponding to the observed signal by correlation coefficient to locate the fault.Finally,experiments are designed to verify the effectiveness of the method.

关 键 词：STFD 滚动轴承 多故障 盲源分离 故障诊断 

分 类 号：TH16[机械工程—机械制造及自动化] TG506[金属学及工艺—金属切削加工及机床]