基于融合分析的感应电机轴承故障检测方法

Bearing Fault Detection Method for Induction Motor Based on Fusion Analysis

根据感应电机轴承发生故障时的振动信号特性以及定子电流特性,求出三相电流的Park矢量模信号,并将其与电机滚动轴承振动信号经解调处理后的包络信号进行融合分析,可以从振动信号与电流信号的融合谱图中有效地提取轴承故障特征信息,并将其作为故障识别的依据。实验结果表明,本文检测方法具有较高的信噪比,提高了诊断的可靠性。

According to characteristics of both the vibration signals and the stator currents when appering a fault in the rolling bearing of the induction motor, Park vector module signal of the three-phase current is calculated, and the envelope of vibration signals from the rolling bearing of the motor is analyzed. Then the fusion method is used for analyzing the Park vector module signal and the envelope signal, and a fusion spectrum is obtained. Experimental results demonstrate that the fault information of the bearing is effectively extracted from the fusion spectrum figure, and the detection method has a better signal-to-noise ratio thus improving the reliability.