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
袁胜智 1李静 1张嘉雨 1金凯1
作者信息
- 1. 海军工程大学兵器工程学院,湖北武汉 430033
- 折叠
摘要
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.
Abstract
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.
关键词
电机轴承/故障诊断/小波包/PSO-BP神经网络Key words
motor bearing/fault diagnosis/wavelet packet/PSO-BP neural network引用本文复制引用
出版年
2024
NETL
NSTL
万方数据