某平台电机轴承智能故障诊断方法的研究与应用

Research and Application of Intelligent Fault Diagnosis Method for Platform Motor Bearing

在某平台系统中,稳定回路电机故障会对系统产生严重影响。为此,基于电机轴承振动信号,提出了一种基于小波包和PSO-BP神经网络的智能故障诊断方法。该方法通过小波包变换提取平台电机轴承频段能量特征作为故障诊断依据,并利用PSO算法优化BP神经网络以提高故障模式识别效率,具有一定的通用性和有效性。

In a platform system,the stability loop motor fault will have a serious impact on the system.Therefore,based on the vibration signal of motor bearing,an intelligent fault diagnosis method based on wavelet packet and PSO-BP neural network is proposed.This method extracts the energy characteristics of the platform motor bearing frequency band by wavelet packet transform as the basis of fault diagnosis,and uses PSO algorithm to optimize BP neural network to improve the efficiency of fault pattern recognition,which has certain universality and effectiveness.