齿轮故障的最优Gabor窗谱检测法

The optimized Gabor window spectrum of gear fault diagnosis detection

齿轮振动信号中存在大量非平稳信号,在用Gabor谱来进行齿轮振动信号时频分析的基础上,针对Gabor变换中窗函数选择的问题,采用熵度量法来选择最优的Gabor窗函数宽度,提高了Gabor变换的时频聚集性;利用谱图的具有特殊的交叉项机理,在自项支撑区域内做出信号的Gabor谱图,有效去除了分量间的交叉项,并在Gabor谱图上来分析齿轮振动信号的时频分布,且与传统的分析方法作了比较。实验结果表明,在优化的Gabor谱图上能很直观地反应存在异常的齿轮及能量随时间的变化,能较易地诊断出齿轮故障。

There is a lot of non-stationary signals in gear vibration signals, which is analyzed by using Gabor spectrum. To resolve the problem of the choice of window,a method based on entropy is proposed to select the optimal Gabor window width,and the time-frequency resolution of Gahor transform is improved. Since the spectrum has its specific mechanism of crossing-item,the Gabor spectrum is calculated in the region of the key support area and the crossing-item is effectively removed, then the Gabor spectrum is used to analysis the time-frequency distribution of vibration signals of gear, and this method is compared with traditional analysis methods. The result shows that the Gabor spectrum can intuitively react abnormal gear and energy changes with time,and easily diagnose the gear fault.