【摘要】 基于信号奇异性检测的小波变换理论 ,利用时间分辨率优化的 Gabor小波变换工具 ,对几种典型故障的波形和轨迹信号的奇异性特征进行了研究。研究表明 ,不同类型的故障信号 ,不仅奇异性指数的数值大小有明显的不同 ,而且奇异点在时间上的分布特征也有显著差异 ,这种差异对轴心轨迹信号尤为明显。因此 ,利用奇异性指数的统计量特征可以有效地区分不同类型的故障更多还原

【Abstract】 Based on the theory of singularity detection by wavelet transformatio n, the statistical features of singularity of several faulty vibration signals a nd orbits are studied with Gabor wavelet transformation, which parameters are op timized for best frequency resolution. It is shown that not only the Lipschitz E xponent, but also the singularity distribution along time, differ between the fa ulty signals, and it is more evident for orbits. So the statistical features of singularity can be used to differentiate vibration faults effectively.更多还原