基于CEEMDAN的最优平滑降噪算法  

OPTIMAL SMOOTHING NOISE REDUCTION ALGORITHM BASED ON CEEMDAN

作　　者：张荣彬 Zhang Rongbin(Dezhou Degong Machinery Co.,Ltd.,Dezhou 253000,Shandong,China)

机构地区：[1]德州德工机械有限公司,山东德州253000

出　　处：《计算机应用与软件》2021年第6期294-298,317,共6页Computer Applications and Software

摘　　要：经验模态分解类算法处理非线性、非平稳信号具有良好的自适应分解能力,可以将复杂信号分解成按照频率由高到低顺序排列的固有模态函数形式,提取分解后的模态函数构造滤波器可以实现对原始信号的降噪处理。针对构造滤波器时对模态函数缺乏最优的筛选指标,从而影响到降噪的准确性与降噪效果,提出一种基于CEEMDAN的最优平滑降噪算法。通过参数调节方式对模态进行筛选,从而设计出性能最优的滤波器实现对信号的降噪处理。通过模拟实验与实际实验,验证了该算法对于转动机械噪声信号具有良好的降噪效果。The empirical mode decomposition algorithm deals with nonlinear and non-stationary signals with good adaptive decomposition ability.It can decompose the complex signal into the form of the intrinsic mode function arranged in order of frequency from high to low.Extracting the decomposed modal function constructing filter can realize the noise reduction processing of the original signal.Aiming at the lack of optimal screening index for modal function when constructing the filter,which affects the accuracy and noise reduction effect of noise reduction,an optimal smoothing noise reduction algorithm based on CEEMDAN is proposed.The modal was screened by adjusting the parameters to design a filter with the best performance to achieve noise reduction of the signal.The simulation experiment and actual experiment of the proposed noise reduction algorithm were carried out,and it is verified that the proposed optimal noise reduction algorithm has good noise reduction effect on the rotating mechanical noise signal.

关 键 词：经验模态分解算法 CEEMDAN 最优平滑降噪 转动机械噪声信号 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]