基于WVD的谱峭度法在轴承故障诊断中的应用

Application of Wigner-Ville-Distribution-Based Spectral Kurtosis Algorithm to Fault Diagnosis of Rolling Bearing

在对基于短时傅里叶变换(STFT)和基于小波变换的谱峭度法分析的基础上,提出了基于Wigner-Ville分布的谱峭度法。将其作为检测工具,利用谱峭度构造最优滤波器提取轴承故障信息。将这三种谱峭度法应用于滚动轴承故障诊断中进行对比分析。分析结果表明,时频分析方法对信号能量的集中程度和时窗与滤波器的选取是影响谱峭度法应用效果的主要因素。该结果对基于时频分析的谱峭度法理论体系的形成及其在故障诊断中的应用具有实际意义。

Based on the analysis of spectral kurtosis using short time Fourier transform(STFT) and wavelet transform(WT),a new algorithm of spectral kurtosis(SK) based on Wigner-Ville distribution(WVD) was established.It was used as the detection tool and a basis for designing optimal detection filters that can efficiently extract the information of rolling bearing fault.The above three algorithms were used to diagnose the fault of a rolling bearing.The results indicate that the concentration extent of signal energy with the time-frequency(TF) method,selection of time windows and filters are dominant factors that affect the algorithm.The analysis results are helpful to forming the theory system of SK algorithms based on the time-frequency analysis and the fault diagnosis.