基于S变换谱核密度估计的齿轮故障诊断

Gear fault diagnosis based on kernel density estimation of S transform spectrum

针对齿轮在故障损伤状态下的振动信号,提出一种基于S变换谱二维核密度估计的冲击特征提取方法,以实现齿轮的故障诊断。该方法首先对包含冲击特征的振动信号进行S变换;然后将S变换谱乘以一个系数后圆整,得到一个整数矩阵;最后以S变换谱的时间和频率构成一个二维随机变量,以整数矩阵中的元素值作为二维随机变量各个采样样本的个数,对二维随机变量进行核密度估计,并最终得到一个二维核密度函数。该核密度函数相当于由S变换谱经过一次平滑去噪的过程获得,其中的噪声得到了有效的抑制,而冲击特征则得到了加强与突显。仿真振动信号和齿轮箱故障振动信号的分析结果表明,该方法能够有效地强化并提取出振动信号中周期性的冲击特征,从而实现齿轮箱相关故障的诊断。

An impact feature extraction method, based on two-dlmensional kernel density estimation for S transform spectrum, is proposed to analyze the vibration signal for gear fault diagnosis. In this approach, S transform is used to process the vibration signal, firstly. Secondly, the obtained S-transform spectrum is multiplied by a factor and then rounded to obtain an integer matrix. Finally, the time and the frequency of the S-transform spectrum are used to construct a two-dimensional random variable, and the elements in the integer matrix are taken as the corresponding sample number of the two-dimensional random variable. The kernel density of the two-dimensional random variable is consequently estimated and a two-dimensional kernel density function is obtained. Specifically, the kernel density function is acquired by the smoothing and denoising procedure of the S transform spectrum, in which the noise is effectively suppressed while the impulse signature is enhanced. By means of the processing of the simulated vibration signal and the gearbox fault vibration signals, results show that the proposed method can extract the periodic impact characteristics from the vibration signal effectively, which means the proposed method can be used for gearbox fault diagnosis.