文章摘要
李常有,徐敏强,郭耸.声信号的主分量分析应用于滚动轴承故障诊断[J].声学技术,2008,(2):271~274
声信号的主分量分析应用于滚动轴承故障诊断
Fault diagnosis of rolling element bearing based on principal component analysis of acoustic signal
投稿时间:2007-04-09  修订日期:2007-07-20
DOI:
中文关键词: 滚动轴承  故障诊断  主分量分析  声信号  包络分析
英文关键词: rolling element bearing  fault diagnosis  principal component analysis  acoustic signal  envelope analysis
基金项目:
作者单位
李常有 哈尔滨工业大学航天学院, 哈尔滨, 150001 
徐敏强 哈尔滨工业大学航天学院, 哈尔滨, 150001 
郭耸 哈尔滨工程大学计算机科学与技术学院, 哈尔滨, 150001 
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中文摘要:
      利用声信号来进行故障诊断具有"采集比较容易,非接触式测取,设备简单,速度快,无须事先粘贴传感器,不影响设备正常工作,易于实现早期预报和在线监测,并可在不易测量振动信号的场合得到广泛应用"等优点。由于外界噪声的影响,有效信息的提取较为困难。采用主分量分析对传声器测取的声信号进行了预处理;在此基础上应用基于Morlet小波变换的包络分析和频谱分析来提取故障特征向量,并以滚动轴承为例进行实验。结果表明,这是诊断滚动轴承早期故障的一种可选方法。
英文摘要:
      Fault diagnosis of using acoustic signal generated by a machine has a lot of advantages,such as easier signal collection,non-contact measurement,no requirement of sticking sensors in advance,no influence of the collection system on the machine,easier actualization of early forecasting and on-line monitoring,and able to be widely used in the occasion where it is difficult to collect vibration signal.However,it is more difficult to extract the characteristic signal due to the effect of environment noise.Ther-efore,the principal component analysis is employed to preprocess the original acoustic signal.Then,En-velope analysis based on Morlet wavelet transform and spectrum analysis are applied to extract the fault characteristic vector.The proposed method has been applied to the fault diagnosis of rolling element bearing.The experimental results show that the proposed method in this paper is effective to diagnose early fault of rolling element bearing.
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