噪声与振动控制

›› 2010, Vol. 30 ›› Issue (1): 82-85.DOI: 10.3969/j.issn.1006-1355.2010.01.082

• 信号处理与故障诊断 • 上一篇    下一篇

《基于变分贝叶斯独立分量分析的故障源盲分离》

范涛1,李志农1,卢纪富2,员险锋1   

  1. （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）
  • 收稿日期:2009-01-04 修回日期:1900-01-01 出版日期:2010-02-18 发布日期:2010-02-18
  • 通讯作者: 范涛

《Blind Separation of Fault Sources Based on Variational Bayesian Independent Component Analysis》

FAN Tao1,LI Zhi-nong1,LU Ji-fu2,YUAN Xian-feng1   

  1. (1.School of Mechanical Engineering, Zhengzhou University, Zhengzhou450001, China；2. School of Civil Engineering, Zhengzhou University, Zhengzhou450001, China)
  • Received:2009-01-04 Revised:1900-01-01 Online:2010-02-18 Published:2010-02-18
  • Contact: FAN Tao

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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

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.

Key words: vibration and wave, blind source separation (BSS), variational bayesian, independent component analysis (ICA), fault diagnosis

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