针对滚动轴承故障诊断提出了EMD阈值降噪法。通过振动传感器获得的轴承振动信号,利用经验模态方法将信号分解为多个IMF分量。因振动信号中含有的噪声主要表现在高频段,所以对IMF分量中的高频分量进行小波阈值降噪,并与IMF分量中低频分量进行重构,实现了振动信号的降噪,有利于轴承故障的判断。 Aiming at the fault diagnosis of rolling bearing, EMD threshold noise reduction method is proposed. The bearing vibration signal obtained by the vibration sensor is decomposed into multiple IMF components by the empirical mode method. Since the noise contained in the vibration signal mainly appears in the high frequency band, the wavelet threshold denoising is performed on the high frequency component in the IMF component, and the low frequency component in the IMF component is reconstructed to realize the noise reduction of the vibration signal, which is beneficial to the bearing Judgment of failure.