EMD降噪和谱峭度法在滚动轴承早期故障诊断中的应用

Application of EMD denoising and spectral kurtosis in early fault diagnosis of rolling element bearings

共振解调是滚动轴承故障诊断中最常用的方法之一,然而其带通滤波器参数的选取通常比较困难。谱峭度法能根据峭度最大化原则自动确定带通滤波器参数,取得了一定的诊断效果,但由于滚动轴承的早期故障信号中含有强烈的背景噪声,诊断效果有时也不够明显。为此,提出一种基于EMD降噪和谱峭度法的滚动轴承早期故障诊断新方法,首先采用基于互相关系数和峭度准则的EMD降噪对采样信号进行预处理,突出高频共振成分,再利用谱峭度法选取最佳带通滤波器参数,最后使用带通滤波和包络解调进行故障诊断,并通过实际工程信号进行了验证。

It is difficult to select the band-pass filter parameters in resonance demodulation which is one of common methods for fault diagnosing of rolling element bearings,but they can be automatically determined by use of spectral kurtosis based on the principle of maxkurtosis.Even though some diagnosis effects have been achieved by this method,it is not obvious enough sometimes due to the strong background noise involved in the early fault signal of rolling element bearings.Therefore,a new early fault diagnosis method based on EMD denoising and spectral kurtosis was proposed.The sampled signal was preprocessed by EMD denoising,combining with the criterions of cross-correlation coefficient and kurtosis to highlight the high-frequency resonance components.The optimal band-pass filter parameters were selected with the help of spectral kurtosis.Then,the fault diagnosis was implemented by band-pass filter and envelope demodulation.The application in a practical engineering signal verified its capability.