基于信息融合技术的异步电机故障诊断研究

为了合理利用异步电动机多个方面的故障特征信息,提高故障诊断的准确性,提出了一种采用异步电动机定子电流、径向(轴向)振动信号等多信息融合的故障诊断方法.对测量的各种信号进行小波分析,利用各个频段的信号能量作为故障特征值.采用D-S证据理论融合各个信息,针对证据理论无法融合高冲突证据的缺陷,引入先验知识对其进行了改进,提高了电机故障诊断准确率.实验结果表明,故障诊断结果可信度明显提高,不确定性显著减小,对异步电动机转子断条故障诊断的准确率达到90%以上.

Study of the Induction Motor Faulted Diagnosis Based on Information Fusion Technology

To improve accuracy of fault diagnosis using integrated motor multi-fault characteristic information,a fault diagnosis method of multi-fault characteristic information fusion was proposed,which include stator current signal,axial vibration signal and radial vibration signal. The measured data were processed by wavelet analysis to obtain the energy eigenvalue at each frequency branch which were defined as the criterion to diagnose the rotor fault. Dempster-Shafer (D-S) evidence theory was used to realize inf...