基于奇异值分解的滚动轴承故障诊断方法  

Fault Diagnosis Method of Rolling Bearing Based on Singular Value Decomposition

作　　者：季景方 Ji Jingfang(School of Automotive Engineering,Hubei University of Automotive Technology,Shiyan 442002,China;Hubei Key Laboratory of Automotive Power Train and Electronic Control,Shiyan 442002,China)

机构地区：[1]湖北汽车工业学院汽车工程学院,湖北十堰442002 [2]汽车动力传动与电子控制湖北省重点实验室,湖北十堰442002

出　　处：《湖北汽车工业学院学报》2024年第3期60-65,共6页Journal of Hubei University Of Automotive Technology

基　　金：汽车零部件技术湖北省协同创新项目(2015XTZX043);湖北省自然科学基金(2022CFB457)。

摘　　要：针对奇异值分解中Hankel矩阵维数和奇异值个数选择的问题,提出了确定矩阵维数和选择奇异值个数的新方法,实现对滚动轴承的故障诊断。将提出的方法应用于实测滚动轴承内圈和外圈故障信号中,通过对信号的降噪处理和包络谱分析,有效消除了实测振动信号中的无用频率成分,提取了信号中包含的轴承故障特征频率。To determine the dimension of Hankel matrix and the number of singular values in singular value decomposition(SVD),a new method to determine the matrix dimension and the number of singular values was proposed to achieve the fault diagnosis of rolling bearings.The proposed method was applied to the measured fault signals of the inner and outer rings of the rolling bearings.Through denoising of the signals and envelope spectrum analysis,the useless frequency components in the measured vibration signals were effectively eliminated,and the fault characteristic frequencies contained in the signals were extracted.

关 键 词：奇异值分解 包络谱分析 奇异值差分序列 故障诊断 

分 类 号：TH17[机械工程—机械制造及自动化]