• CN:11-2187/TH
  • ISSN:0577-6686

›› 2011, Vol. 47 ›› Issue (3): 55-62.

• 论文 • 上一篇    下一篇

基于噪声辅助分析的总体局部均值分解方法

程军圣;张亢;杨宇   

  1. 湖南大学汽车车身先进设计制造国家重点实验室
  • 发布日期:2011-02-05

Ensemble Local Mean Decomposition Method Based on Noise-assisted Analysis

CHENG Junsheng;ZHANG Kang;YANG Yu   

  1. State key Laboratory of Advanced Design and Manufacture for Vehicle Body, Hunan University
  • Published:2011-02-05

摘要: 局部均值分解(Local mean decomposition, LMD)方法是一种新的自适应时频分析方法,但在其实现过程中会发生模态混淆现象,使分析结果失真。通过数值试验得到了LMD对白噪声的滤波器组结构,并在此基础上,针对模态混淆现象提出总体局部均值分解(Ensemble local mean decomposition, ELMD)方法。在该方法中添加不同的白噪声到目标信号,分别对加噪后的信号进行LMD分解,最后将多次分解结果的平均值作为最终的分解结果。对仿真信号和试验转子局部碰摩信号进行分析,结果表明ELMD方法能有效地克服原LMD方法的模态混淆现象。

关键词: 白噪声, 局部均值分解, 滤波器组, 模态混淆, 总体局部均值分解

Abstract: The local mean decomposition (LMD) is a newly self-adaptive time-frequency analysis method. Mode mixing phenomenon which makes the decomposition results distortion may be produced when LMD is performed. The filter bank structure of LMD in white noise is obtained by numerical experiments, and based on this, the ensemble local mean decomposition method (ELMD) is proposed to overcome the shortcomings of mode mixing. In ELMD, different white noise is added to the targeted signal. The noise-added signal is decomposed by using LMD. Several decomposed results is severed as the final decomposition result. The analytical results from simulated signal and experimental rotor local rub-impact signal demonstrate that the ELMD method can be used to improve the mode mixing of the original LMD method effectively.

Key words: Ensemble local mean decomposition, Filter bank, Local mean decomposition, Mode mixing, White noise

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