• CN:11-2187/TH
  • ISSN:0577-6686

›› 2008, Vol. 44 ›› Issue (3): 135-142.

• 论文 • 上一篇    下一篇

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小波变换中经验模态分解的基波检测及其在机械系统中的应用

秦毅;秦树人;毛永芳   

  1. 重庆大学机械工程学院
  • 发布日期:2008-03-15

Fundamental Wave Detection Based on Wavelet Transform and Empirical Mode Decomposition with Application in Mechanical System

QIN Yi;QIN Shuren;MAO Yongfang   

  1. College of Mechanical Engineering, Chongqing University
  • Published:2008-03-15

摘要: 针对Mallat算法中存在的频率混叠现象,提出一种应用小波变换和经验模态分解(Empirical mode decomposition,EMD)检测基波的新方法。应用离散二进小波变换将谐波信号分解成不同频带的子带信号,并确定了最佳分解级数。对包含基频成分的子带信号进行单子带重构,再利用经验模态分解就能提取出基波,最后在时域上采用最小二乘法估计基频和幅值。多种方法的仿真比较和工程应用的效果表明,所提方法能有效地提取出基波,频率和幅值的测量具有很高的精度。

关键词: Mallat算法, 基波检测, 经验模态分解, 频率混叠, 小波变换

Abstract: Aiming at conquering the spectral aliasing in the Mallat algorithm, a new method for fundamental wave detection with the wavelet transform and empirical mode decomposition (EMD) is proposed. The discrete dyadic wavelet transform decomposes the harmonic signal into sub-band signals of different frequency-bands, and the optimal decomposition level is determined. Then the single band reconstruction is performed to the sub-band signal including fundamental frequency component, and the fundamental wave can be extracted by empirical mode decomposition. Finally, the fundamental frequency and amplitude of the signal are estimated by the least square method in the time domain. Through the comparison of simulation results generated by different methods and the application, it is shown that the fundamental wave can be extracted effectively with this method, so that the frequency measurement and amplitude measurement are of high accuracy.

Key words: Empirical mode decomposition, Fundamental wave detection, Mallat algorithm, Spectral aliasing, Wavelet transform

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