首页 | 本学科首页   官方微博 | 高级检索  
     

基于小波包特征向量弹性BP算法的故障诊断
引用本文:祝晓燕,王继选,刘小贞,赵冉. 基于小波包特征向量弹性BP算法的故障诊断[J]. 汽轮机技术, 2008, 50(6)
作者姓名:祝晓燕  王继选  刘小贞  赵冉
作者单位:华北电力大学,保定,071003;鹤壁丰鹤发电有限责任公司,鹤壁,458008;邯郸职业技术学院,邯郸,056001
基金项目:国家自然科学基金资助项目(50676031)
摘    要:为精确诊断转子故障,采用了基于小波包能量特征向量的弹性BP神经网络和最速下降BP算法神经网络的故障诊断方法,对采集到的信号进行3层小波包分解,构造小波包特征向量,对样本进行3层BP网络训练,实现智能化故障诊断。结果表明采用改进的BP算法优于最速下降BP算法,训练的网络可以很好地诊断转子故障。

关 键 词:神经网络  转子  故障诊断  弹性BP算法  小波包特征向量

Fault Diagnosis of Rotor Based on Wavelet Packet Energy Eigenvector Resilient Back-propagation Neural Network
ZHU Xiao-yan,WANG Ji-xuan,LIU Xiao-zhen,ZHAO Ran. Fault Diagnosis of Rotor Based on Wavelet Packet Energy Eigenvector Resilient Back-propagation Neural Network[J]. Turbine Technology, 2008, 50(6)
Authors:ZHU Xiao-yan  WANG Ji-xuan  LIU Xiao-zhen  ZHAO Ran
Abstract:In order to diagnose the rotor fault precisely,this paper applies the resilient back propagation neural network and steepest descent back propagation neural network which based on wavelet packet energy eigenvector.It adopts three-layer wavelet packet to decompose the signal which acquisited from the rotor experiment,and constructs the wavelet packet energy eigenvector,take the energy eigenvector as fault samples to train three-layer BP neural network,finally it realizes the intelligent fault diagnosis.The r...
Keywords:neural network  rotor  fault diagnosis  resilient back-propagation  wavelet packet energy eigenvector  
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号