[1]杨伟力,于阳阳,罗达灿.基于小波包和PSO-Elman神经网络的滚动轴承故障诊断[J].机械与电子,2016,(05):13-17.
　YANG Weili,YU Yangyang,LUO Dacan.Rolling Bearing Fault Diagnosis Using Wavelet Packet Analysis and PSO-Elman Neural Network[J].Machinery & Electronics,2016,(05):13-17.
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基于小波包和PSO-Elman神经网络的滚动轴承故障诊断
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2016年05期
页码:
13-17
栏目:
设计与研究
出版日期:
2016-05-25

文章信息/Info

Title:
Rolling Bearing Fault Diagnosis Using Wavelet Packet Analysis and PSO-Elman Neural Network
作者:
杨伟力; 于阳阳; 罗达灿
(贵州民族大学贵州省模式识别与智能系统重点实验室，贵州 贵阳 550025）
Author(s):
YANG Weili; YU Yangyang; LUO Dacan
(Key Laboratory of Pattern Recognition and Intelligent Systems of Guizhou Province，Guizhou Minzu University，Guiyang 550025，China）
关键词:
故障诊断; 滚动轴承; 小波包; PSO-Elman神经网络
Keywords:
fault diagnosis; rolling bearing; wavelet packet; PSO-Elman neural network
分类号:
TH133.3；TP183
文献标志码:
A
摘要:
针对滚动轴承的故障诊断，分析滚动轴承故障机理及特点，提出基于小波包分析的滚动轴承振动信号的特征向量提取算法，并建立PSO-Elman神经网络进行故障诊断和识别。将滚动轴承故障振动信号进行小波包分解，构造频带能量谱作为特征向量，输入PSO-Elman神经网络对故障进行识别。试验结果表明，基于小波包分析和PSO-Elman神经网络相结合的方法可准确地实现滚动轴承的故障诊断。
Abstract:
For the fault diagnosis of rolling bearing , the paper analyses the mechanism and characteristics of rolling bearing faults,presents an algorithm based on wavelet packet analysis of rolling bearing vibration signal feature vector extraction,and establishes the PSO-Elman neural network for fault diagnosis and identification.Wavelet package decomposition is performed for the fault vibration signal of the rolling bearing.The frequency band energy spectrum serves as the feature vector. It was input to the PSO-Elman neural network for fault identification.The test results show that the method based on the wavelet packet analysis and PSO-Elman neural network can accurately achieve the rolling bearing fault diagnosis.

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备注/Memo

备注/Memo:
收稿日期：2016-03-22
基金项目：贵州省科技合作计划课题(黔科合J字LKM[2012]09，黔科合LH字[2015]7208，黔科合LH字[2015]7216，黔科合LH字[2015]7217)；贵州省教育厅自然科学研究项目（黔教合KY字[2015]428）；贵州民族大学科研课题(15XJ008)
作者简介：杨伟力（1990-），男，仡佬族，贵州务川人，助教，研究方向为信息融合，智能机器人理论与技术。
更新日期/Last Update: 2016-05-25