Abstract：Time-varing rotational speed and gear noise are key problems of rolling element bearing fault diagnosis in rotating machinery.Although there are some effective algorithms for them,the problems that rely on auxiliary equipment and complicated steps are still outstanding.A new method of rolling element bearing fault diagnosis based on Instantaneous Dominant Meshing Multiply(IDMM) and Empirical Mode Decomposition (EMD) is proposed.The new method firstly extract IDMM from time-frequency representation by peak searching algorithm,IDMM is equivalent to bearing rotating frequency,signal resampling by IDMM and mixed signal.Then,the method decomposes resampled signal by EMD,calculates cross-correlation coefficient between IMFs and resampled signal and selects IMFs by threshold value of cross-correlation coefficient.Finally,the selected IMFs are analyzed with envelope spectrum.The effectiveness of the proposed method has been validated by both simulated and experimental bearing vibration signals.
赵德尊 李建勇 程卫东 . 变转速及齿轮噪源干扰下基于IDMM与EMD的滚动轴承故障诊断方法[J]. 振动与冲击, 2016, 35(10): 101-107.
ZHAO Dezun LI Jianyong CHENG Weidong. The method of rolling element bearing fault diagnosis based on IDMM and EMD under time-varing rotational speed and gear noise. JOURNAL OF VIBRATION AND SHOCK, 2016, 35(10): 101-107.
