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基于经验模态分解的算法改进
引用本文:赵文忠,张传军. 基于经验模态分解的算法改进[J]. 自动化与仪器仪表, 2009, 0(5): 25-26,33
作者姓名:赵文忠  张传军
作者单位:1. 河西学院机电工程系,甘肃张掖,734000
2. 无锡亿能电气有限公司,江苏无锡,214002
摘    要:
经验模态分解(EMD)算法是Hilbert—Huang变换(HHT)的核心算法,它的分解效果依赖于采样频率的选择,介绍一种新的EMD的采样频率选取方法,并通过仿真信号实验表明该方法分解信号更完全,对电力系统谐波检测分析有一定的实际应用价值。

关 键 词:振动信号  采样频率  EMD

New algorithm of empirical mode decomposition
ZHAO Wen-zhong,ZHANG Chuan-jun. New algorithm of empirical mode decomposition[J]. Automation & Instrumentation, 2009, 0(5): 25-26,33
Authors:ZHAO Wen-zhong  ZHANG Chuan-jun
Abstract:
Empirical Mode Decomposition (EMD) algorithm is the Hilbert-Huang Transform (HHT) of the core algorithm, which relies on the decomposition of the effect of the choice of sampling frequency EMD introduced a new method of selecting the sampling frequency and signal through the simulation experiments show that the method is more complete decomposition of the signal,on the power system harmonic analysis of the practical application of a certain value.
Keywords:EMD
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