QIU Bin, JIANG Haoran, ZHOU Pengxiang, et al. AEEMD harmonic detection algorithm based on improved wavelet threshold denoising[J]. 2020, 39(7): 115-118. DOI: 10.13873/J.1000-9787(2020)07-0115-04.
改进型小波阈值去噪的AEEMD谐波检测算法
摘要
为消除采样信号中噪声对自适应集合经验模态分解(AEEMD)的影响
提出一种基于改进型小波阈值去噪的AEEMD谐波检测算法。采用新的公式处理有效的小波系数
采用软硬阈值结合的方法消除噪声
再进行AEEMD。经MATLAB仿真分析
验证所提方法可以有效地消除随机噪声
并将分解效率提高了2. 06倍
有效分量与原始信号的相关度平均提升了19. 36%
改进后的方法能够很好地提高分解效率
从而验证了所提出的算法是可行和有效的。
Abstract
In order to eliminate the influence of noise on adaptive ensamble empirical mode decomposition(AEEMD) in sampling signal
an AEEMD harmonic detection algorithm based on improved wavelet threshold denoising is proposed. The method uses new formula to deal with the effective wavelet coefficients
and uses the method of soft and hard threshold combination to eliminate the noise
and then carries out AEEMD decomposition.The simulation results show that the proposed method can effectively eliminate the random noise and improve the decomposition efficiency by 2. 06 times. The correlation between the effective component and the original signal is improved by 19. 36 %. The improved method can improve the decomposition efficiency well
so as to verify that the proposed algorithm is feasible and effective.