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基于小波包能量谱的滚动轴承故障检测

Fault Diagnosis of Rolling Bearings Based on Wavelet Packet Energy Spectrum

  • 摘要: 小波包具有对非平稳信号进行局部化分析的功能,可解决小波分析在高频部分分辨率差的问题,据此,提出一种基于小波包能量谱的滚动轴承故障分析方法。首先,将振动数据小波包分解为多个子频带,求出各频带的能量比例;然后,比较正常振动信号与故障振动信号的频带能量谱,识别出故障的频带;在此基础上,重构故障频带,运用Hilbert变换对重构信号包络解调,提取出故障频率。试验结果验证了采用小波包能量谱对滚动轴承故障检测的可行性。

     

    Abstract: Wavelet packet,which has the function of analyzing non-stationary signal locally, can solve the problem of poor resolution in high frequency part with wavelet analysis. Hereby, a method of rolling bearings fault diagnosis based on wavelet packet energy spectrum was proposed. Firstly, the vibration signals were decomposed into individual frequency bands by wavelet packet, and energy ratio of each band was obtained. Then, the energy spectrum scale between the normal vibration signal and fault vibration signal was compared to identify the fault frequency band. The fault signal frequency band were reconstructed, the reconstructed signals envelope were demodulated with Hilbert transform, and the fault frequency was extracted. Experimental results verify the feasibility of the wavelet packet energy spectrum for fault detection of rolling bearing.

     

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