自相关结合灰色关联度的轴承早期故障诊断方法

Early Fault Diagnosis of Bearing Coupling Autocorrelation and Grey Relational Degree

针对滚动轴承性能衰退指标敏感度低且退化起始点难以检测的问题,本文提出了自相关函数结合灰色关联度(Autocorrelation function and gray relational degree,AF-GRD)的轴承早期故障诊断方法。首先,基于希尔伯特变换和自相关函数处理轴承全寿命数据样本组获得自相关系列函数。然后,提取轴承运行初期的第一组数据作为参考样本,计算其余样本和参考样本的灰色关联度并构建轴承性能衰退指标。最后,根据该指标的变化趋势和健康阈值确定轴承早期故障发生的时间段,截取该时段的数据样本进行希尔伯特包络谱分析实现轴承早期故障诊断。利用实验室数据库完成对轴承早期故障诊断,结果表明:所提方法敏感度高而且可以完成轴承早期退化检测。

Aiming at the low sensitivity of rolling bearing performance degradation index and difficulty in determining the starting point of degradation,an early fault diagnosis method of bearing coupling autocorrelation function and gray relational degree(AF-GRD)is proposed.Firstly,the autocorrelation series function is obtained based on the Hilbert transform and the AF by processing the life data sample group of bearing.Then,the first set of data in the early stage of bearing operation was extracted as a reference sample,the GRD between the remaining samples and the reference sample was calculated and the bearing performance degradation index was constructed.Finally,the time period of the early fault of bearing is determined according to the change in index and health threshold,the data sample of this period are intercepted for Hilbert envelope spectrum analysis to realize early fault diagnosis.Using the laboratory database to complete early fault diagnosis of the bearing,the results show that AF-GRD has high sensitivity and can detect the early degradation of bearings.