基于最小二乘拟合的电机轴承故障诊断新方法

New Method of Bearing Fault Diagnosis Based on Least Square Fitting

轴承故障诊断的方法有多种,但要在复杂干扰情况全面地诊断、精确地了解电机轴承的故障程度,传统的诊断方法很难满足要求。以电机定子电流信号为分析源,利用小波包变换等数字信号处理技术,在实验中得到了一个与轴承故障程度有良好线性关系的参数。此参数的获得为更精确地诊断轴承设备的损坏程度提供了新的思路。

There are many ways to bearing fault diagnosis, but if it requires accurate diagnosis, fully reflecting characteristics of motor fault, and less interference, traditional methods is very difficult to meet. Motor current signals are analyzed by wavelet packet and a parameter which has a good linear relationship with serious degree of fault is got. A new path for diagnos equipment damage degree in future is provided by this approach.