Research on feature extraction of impulse signal using Walsh transform
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摘要: 提出使用Walsh变换和小波包相结合的方法,对滚动轴承故障产生的冲击信号序列提取故障特征, 并给出了计算的有效算法. 对滚动轴承故障特征分析和计算表明,用改进小波包分解、重构公式能有效地剔除冲击信号序列中高频共振信号和噪声, 使用快速Walsh变换(FWT)求取其功率谱,优于Fourier变换,可很好地提取故障特征,仿真和实际数据计算的结果,证实了上述方法的有效性.Abstract: Compared with Fourier transform, the amplitude of the impulse signal power spectrum of Walsh transform was larger than that of Fourier transform, and the calculation speed of Walsh transform was faster. Wavelet packet analysis could reduce noise of the signal and filter unnecessary signals and characterization of fault signal was put forward. With Walsh transform and wavelet packet analysis, characterization of fault better could be obtained. Bearing vibration signal included fault frequency features when rolling bearing had fault. The Walsh power spectrum of the rolling bearing with fault signal was calculated by using the Walsh transform and discussed for bearing fault diagnosis. Both simulation and testing results indicate that Walsh transform and wavelet packet analysis are effective method in the diagnosis of bearing various faults.
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Key words:
- feature extraction /
- rolling bearing /
- fault diagnosis /
- impulse signal /
- Walsh transform
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