滚动轴承振动信号的小波奇异性故障检测研究

该文以滚动轴承振动信号为分析对象 ,基于小波奇异性分析原理进行滚动轴承故障检测新方法的研究。通过求解待测信号的小波变换极大模来检测和识别信号中奇异点位置和奇异性大小 ,以及对噪声极大模的抑制处理 ,达到抑制或消除噪声的目的 ;最后 ,在剩余小波极大模的基础上进行信号重构 ,展现原待测信号中的故障信号模式。通过对铁路货车车轮用滚柱轴承振动信号的分析表明 ,此方法在大幅度地提高信噪比的同时 ,对由轴承损伤冲击造成的信号突变仍保持了较高的灵敏度和分辨率。为滚动轴承故障检测打下了良好的基础。

Study on Vibration Signal Singularity Analysis by Wavelet for Rolling Element Bearing Defect Detection

Based on signal singularity analysis of wavelet, a new method of rolling element bearing defect detecting is proposed in this paper. The method is conducted in three procedures. Firstly, singularity analysis of vibration signal is carried out by detecting locations and amplitudes of wavelet transform maxima of the signal. Secondly, noise singularities are removed by canceling wavelet transform maxima of noise. Lastly, the signal is recovered from the remained wavelet transform maxima. Defect detection tests of railway rolling element bearing shows that the proposed method improves signal noise rate significantly, meanwhile and holds high resolution for locations of signal singularities, which were caused by impacts between defect and its mating surface in the bearing. The proposed method shows its broad potential in rolling element bearing fault detection.