基于EMD细化包络谱分析在轴承故障诊断中的应用

将经验模式分解(empirical mode decomposition,EMD)、Hilbert变换和细化(ZOOM)技术结合在一起。通过EMD分解的自适应滤波算法,避免了依靠经验来设置带通滤波器的中心频率和带宽,或者用小波方法对信号进行分解时,需要预先确定基函数和分解尺度的缺点,从而为计算包络谱的细化提供了一种简易算法。结果表明,基于经验模式分解自适应滤波的滚动轴承振动信号解调方法能够有效地突出故障特征频率成分,避免误诊断。

Zooming Envelope Spectrum Analysis Based on EMD in Rolling Bearing Fault Diagnosis

Combines the empirical mode decomposition with Hilbert transform and Zoom-FFT technologies together.The adaptive filtering method based on EMD provides a simple algorithm for calculating envelope spectrum zoom.This algorithm avoids setting the center frequency and bandwidth of band-pass filter relying on experience,and overcomes the shortcomings of pre-determined basis functions and decomposition scale when used the method of wavelet analysis of signals.The experimental results show that the rolling bearing...