J4 ›› 2009, Vol. 27 ›› Issue (05): 487-.

• 论文 • 上一篇    下一篇

经验模态分解的时频分析方法及其应用

徐世艳   

  1. 辽源职业技术学院 机电工程系,吉林 辽源 136201
  • 出版日期:2009-09-20 发布日期:2009-11-03
  • 通讯作者: 徐世艳(1967— ),女,吉林农安人,辽源职业技术学院副教授,主要从事物理学研究 E-mail:xushiy-an00@sina.com
  • 作者简介:徐世艳(1967— ),女,吉林农安人,辽源职业技术学院副教授,主要从事物理学研究,(Tel)86437-2880268(Email)xushiy-an00@sina.com

TimeFrequency Analysis Method and Its Application Based on Empirical Mode Decomposition

XU Shi-yan   

  1. Department of Mechatronics Engineering,Liaoyuan Vocational and Technical College,Liaoyuan 136201,China
  • Online:2009-09-20 Published:2009-11-03

摘要:

研究了经验模态分解与希尔伯特变换相结合提取信号特征参数的方法,并对其性能进行了分析。给出了经验模态分解时频特性分析方法及步骤,并用该方法对瞬态信号特征提取及信号趋势提取进行了研究,仿真实验验证了该方法的可行性和有效性。将经验模态分解时频分析方法应用于信号的趋势提取领域,验证了此时频分析方法的有效性以及反映信号局部时频特征的独特优点。

关键词: 经验模态分解, 时频分析, 特征参数, 瞬态信号

Abstract:

For better signal processing and feature extracting of nonstationary signal, timefrequency analysis is one of the top interests and more and more research has been put on this topic. For the limitations of the conventional methods of timerequency analysis, a novel method of timefrequency analysis is analyzed which is applicable to nonstabilization and nonlinear signal. Empirical mode decomposition algorithm which is used to extract features of signals through utilizing the empirical mode decomposition and hilbert transformation are proposed and its characteristics are analyzed. The analysis method and steps of empirical mode decomposition timefrequency characteristic is presented. To demonstrate the validity and unique virtue of empirical mode decomposition timefrequency analysis method, the transient signal features abstraction and signal tendency abstraction are studied by the method. Simulation results have shown the feasibility and validity of the method. Lastly, timefrequency analytic method based on empirical mode decomposition is used to extract of signals trend component and to demonstrate the efficiency and superiority of this new timefrequency analytic method.

Key words: empirical mode decomposition, timefrequency analysis, characteristics parameters, transient signal

中图分类号: 

  • TN911.7