噪声与振动控制

›› 2011, Vol. 31 ›› Issue (6): 53-56.DOI: 10.3969/j.issn.1006-1355-2011.05.012

• 2.振动理论与数值解法 • 上一篇    下一篇

利用改进的EMD和随机减量法识别模态参数

彭程,张立民,李原辉,邱飞力   

  1. （ 西南交通大学 牵引动力国家重点实验室， 成都 610031 ）
  • 收稿日期:2010-12-17 修回日期:2011-02-14 出版日期:2011-12-18 发布日期:2011-12-18
  • 通讯作者: 彭程

Identification of Modal Parameters Using Improved EMD and Random Decrement Method

PENG Cheng,ZHANG Li-min,LI Yuan-Hui,QIU Fei-Li   

  1. ( Traction Power Lab, Southwest Jiao tong University, Chengdu 610031, China )
  • Received:2010-12-17 Revised:2011-02-14 Online:2011-12-18 Published:2011-12-18
  • Contact: PENG Cheng

摘要： 对振动信号进行小波去噪，克服环境噪声的干扰，提高EMD的质量，利用相关系数去除虚伪分量，然后利用随机减量法和ITD法识别出列车地板的固有频率和阻尼比。将此方法识别结果与LMS商业软件识别结果进行对比，频率相对误差不超过6 %，阻尼比相对误差不超过7 %。由此说明该方法具有较高的识别精度。

关键词: 振动与波, 模态参数识别, 小波, EMD, 随机减量法, ITD

Abstract: In order to overcome the interference of environmental noise and improve the quality of EMD, the wavelet method is used to eliminate the noise signal. The correlation coefficients are applied to remove the pseudo components. And then, the random decrement method and ITD method are used to identify the natural frequency and damping ratio of train’s floor. Compared the identification results with those from LMS commercial software, it is found that the relative error of frequency is less than 5%, the relative error of damping ratio is less than 7%. This shows that the method has high precision of identification.

Key words: vibration and wave, modal parameter identification, wavelet, EMD, random decrement method, ITD

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