摘要
分别用小波分解、小波包分解和EMD分解处理滚动轴承故障数据,并结合Hilbert变换进行包络谱分析实现滚动轴承故障诊断。对滚动轴承故障数据进行小波阈值降噪。小波阈值降噪后分别进行小波分解、小波包分解和EMD分解。分别求出小波分解、小波包分解和EMD分解后各个频带的能量谱。再根据能量谱确定故障频带范围并对其进行信号重构。采用Hilbert变换对重构信号进行包络谱分析实现滚动轴承故障诊断。通过对滚动轴承内圈故障信号的分析验证了小波分解、小波包分解和EMD分解结合Hilbert变换进行包络谱分析的滚动轴承故障诊断方法的有效性。
Wavelet decomposition,wavelet packet decomposition and EMD decomposition are used to deal with rolling bearing fault data,and the Hilbert transform is used to carry out envelope spectrum analysis to realize rolling bearing fault diagnosis.Wavelet threshold noise reduction is applied to rolling bearing fault data.Wavelet decomposition,Wavelet Packet Decomposition and EMD Decomposition are carried out respectively after wavelet threshold denoising.The energy spectrum of each band after wavelet decomposition,wavelet packet decomposition and EMD decomposition are obtained respectively.And then the fault band is determined according to the energy spectrum and the signal is reconstructed.The Hilbert transform is used to carry out envelope spectrum analysis of the reconstructed signal to realize fault diagnosis of rolling bearing.The validity of the method for fault diagnosis of rolling bearing based on wavelet analysis,wavelet packet decomposition and EMD decomposition is analyzed by analyzing the fault signal of inner bearing of rolling bearing.
出处
《煤矿机械》
2017年第2期155-159,共5页
Coal Mine Machinery
关键词
故障诊断
小波分解
小波包分解
EMD分解
HILBERT变换
fault diagnosis
wavelet decomposition
wavelet packet decomposition
EMD decomposition
Hilbert transform
