首页 | 本学科首页   官方微博 | 高级检索  
     

基于变分贝叶斯独立分量分析的故障源盲分离
引用本文:范涛,李志农,卢纪富,员险锋.基于变分贝叶斯独立分量分析的故障源盲分离[J].噪声与振动控制,2010,30(1):82-85.
作者姓名:范涛  李志农  卢纪富  员险锋
作者单位:(1. 郑州大学机械工程学院,郑州450001;2. 郑州大学土木工程学院,郑州450001)
基金项目:国家自然科学基金,河南省教育厅自然科学基金 
摘    要:提出一种基于变分贝叶斯独立分量分析的故障源盲分离方法,该方法可直接对噪声干扰的机械源信号进行有效分离,即不需要将未知噪声看成一种独立源,也不需要进行消噪预处理。并将该方法与传统的机械源分离方法进行对比实验,实验结果表明该方法是非常有效的。

关 键 词:振动与波  盲源分离  变分贝叶斯  独立分量分析  故障诊断  
收稿时间:2009-1-4

Blind Separation of Fault Sources Based on Variational Bayesian Independent Component Analysis
FAN Tao,LI Zhi-nong,LU Ji-fu,YUAN Xian-feng.Blind Separation of Fault Sources Based on Variational Bayesian Independent Component Analysis[J].Noise and Vibration Control,2010,30(1):82-85.
Authors:FAN Tao  LI Zhi-nong  LU Ji-fu  YUAN Xian-feng
Affiliation:(1.School of Mechanical Engineering, Zhengzhou University, Zhengzhou450001, China;2. School of Civil Engineering, Zhengzhou University, Zhengzhou450001, China)
Abstract:A blind separation method of rotor' s fault sources based on variational Bayesian independent component analysis ( VBICA ) is proposed. This method can directly separate the signals of mechanical sources in noisy environment. In this method, the unknown noise need not to be regarded as an independent source, and the denoising preprocessing is not necessary either. Then, this method is compared with the traditional blind source separation method for machine faults. Finally, this method is applied for the fault sources separation of rotor system. Experiment results show that this method is very effective.
Keywords:vibration and wave  blind source separation (BSS)  variational bayesian  independent component analysis (ICA)  fault diagnosis
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《噪声与振动控制》浏览原始摘要信息
点击此处可从《噪声与振动控制》下载全文
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