基于改进EMD的信号降噪方法  

Signal Denoising Method Based On Improved EMD

作　　者：王强[1] 王莉[1] 陈晨[1] 李伟伟[1] WANG Qiang;WANG Li;CHEN Chen;LI Wei-wei(Air force Engineering University,School of Air and Missile Defense,Xi’an 710051,China)

机构地区：[1]空军工程大学防空反导学院,西安710051

出　　处：《火力与指挥控制》2017年第8期111-114,共4页Fire Control & Command Control

摘　　要：经验模态分解(Empirical Mode Decomposition,EMD)算法作为新型时频分析方法受到广泛关注,它基于信号的极值特性处理信号,具有自适应强、无需预先确定基函数的优点。但EMD算法本身仍存在模态混叠及EMD强制降噪法易导致信号失真等一系列问题。针对EMD算法的缺陷,提出基于自相关函数的集合经验模态分解方法(Ensemble Empirical Mode Decomposition,EEMD)与小波阈值降噪相结合的改进算法。首先利用自相关函数对高频固有模态函数(Intrinsic Mode Function,IMF)进行选择,然后利用小波阈值降噪法为EEMD设定阈值,最后将改进算法用于信号降噪,并与快速傅里叶变换(FFT)算法、小波阈值算法以及EMD强制降噪算法进行比较。该方法的优点是克服了EMD算法的不足,避免了模态混叠现象,有效地保留了高频信号中分量,降噪效果更好。Empirical mode decomposition algorithm is widely concerned with the new timefrequency analysis method.It is based on the characteristic of signal processing,which has theadvantages of strong adaptability and no need to determine the basis function in advance.However,thereare still a series of problems,such as mode mixing and signal distortion because of EMD noisereduction method.In view of the defects of EMD algorithm,this paper proposes an improved algorithmbased on the combination of Ensemble Empirical Mode Decomposition and wavelet threshold denoisingalgorithm.First of all,it uses the correlation function to choose the high frequency of Intrinsic ModeFunction;Then,the wavelet threshold is setting a threshold for the EEMD;Finally,the improvedalgorithm is used for signal denoising and compared with the Fast Fourier Transform algorithm,waveletthreshold algorithm and forced denoising of EMD.The advantages of the method overcomes theshortcomings of the EMD algorithm and avoids the mode mixing phenomenon.It also effectively retainsthe high frequency signal component.The noise reduction effect is better than the previous method.

关 键 词：EMD EEMD 小波阈值降噪 IMF 

分 类 号：TM935[电气工程—电力电子与电力传动]