一种抑制维格纳分布交叉项的方法及在故障诊断中应用

A Method to Suppress Cross-terms of Wigner-Ville Distribution and Its Application in Fault Diagnosis

分析了滚动轴承典型故障产生机理及其故障特征频率,提出一种利用自适应短时傅里叶变换(ASTFT)抑制维格纳分布(WVD)交叉项的故障诊断方法。该方法首先对信号进行ASTFT得到信号的ASTFT谱图,然后将ASTFT谱作为窗函数对信号的WVD进行加窗处理,从而有效消除掉WVD中的交叉项。仿真实验验证了该方法的优越性。将该方法应用于轴承的故障诊断,结果表明,该方法用于故障特征提取是有效的。

The principles and characteristic frequency of typical faults of rolling bearings were analyzed,and a new fault diagnosis method to suppress cross--terms of WVD using adaptive short--time Fourier transform （ASTFT） spectrum was put forward. Firstly, the signal ASTFT spectrum which can determine the signal component positions in the time--frequency plane was obtained. Then, window function, ASTFT spectrum, was selected to process the signal WVD. Thus the cross--term interference can be effectively restrained. The simulation results show that a better resolution and more effective suppression of cross--term interference can be obtained. At last, the proposed method is applied to the fault diagnosis of bearing, the experimental results show the proposed method is effective in feature extraction.