基于二阶包络逆EMD算法改进与实现

PDF(1606 KB)

振动与冲击 ›› 2017, Vol. 36 ›› Issue (6) : 128-133.

论文

基于二阶包络逆EMD算法改进与实现

何经伟，胡维平，莫家玲

作者信息 +

Improvement and implementation of inverse EMD algorithm based on second order envelope

HE Jingwei,HU Weiping,MO Jialing

Author information +

文章历史 +

摘要

在分析经典EMD(Empirical Mode Decomposition)和高阶极值点逆向筛分EMD方法的基础上，提出了一种基于二阶包络逆EMD的改进方法。该方法结合标准EMD与逆EMD的良好属性，采用一阶、二阶包络，通过给定条件在筛分过程选择最优包络均值进行筛分。实验结果表明：该方法适用于分解频率差值较低的多分量信号且减小高频分量误差；有效地减小估计误差及抑制多余IMF分量；以最优包络作为筛分包络，EMD分解效果更佳。

Abstract

On the basis of analysing the classic empirical mode decomposition (EMD) method and the inverse EMD method in which the high-order extreme value point is used in reverse screening,a method based on second order envelope inverse EMD was proposed.The method integrates the good properties of the classic EMD and inverse EMD.Making use of the first and second order envelope and introducing certain conditions in the screening process,the mean value of an optimal envelope was chosen for screening.The experimental results show that the method is suitable for being applied to decompose multi-component signals with low frequency difference between components.It can reduce the error of high frequency components,effectively decrease the estimation error and restrain the excess IMF components.The EMD decomposition effect will be better when the optimal envelope is adopted in screening.

导出引用

何经伟，胡维平，莫家玲. 基于二阶包络逆EMD算法改进与实现[J]. 振动与冲击, 2017, 36(6): 128-133

HE Jingwei,HU Weiping,MO Jialing. Improvement and implementation of inverse EMD algorithm based on second order envelope[J]. Journal of Vibration and Shock, 2017, 36(6): 128-133

参考文献

[1] Huang N E, Shen Z, Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[C]//Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences. The Royal Society, 1998, 454(1971): 903-995.
[2] 徐冠雷, 王孝通, 徐晓刚, 等. 多分量到单分量可用 EMD 分解的条件及判据[J]. 自然科学进展, 2006, 16(10): 1356-1360.
XU Guan-lei, WANG Xiao-tong, XU Xiao-gang, et al. Conditions and criteria of EMD for multi-component to single component [J]. Progress in Natural Science, 2006, 16(10): 1356-1360.
[3] Kopsinis Y, McLaughlin S. Enhanced empirical mode decomposition using a novel sifting-based interpolation points detection[C]//Statistical Signal Processing, 2007. SSP'07. IEEE/SP 14th Workshop on. IEEE, 2007: 725-729.
[4] Kopsinis Y, McLaughlin S. Investigation and performance enhancement of the empirical mode decomposition method based on a heuristic search optimization approach[J]. Signal Processing, IEEE Transactions on, 2008, 56(1): 1-13.
[5] Guanlei X, Xiaotong W, Xiaogang X. Neighborhood limited empirical mode decomposition and application in image processing[C]//Image and Graphics, 2007. ICIG 2007. Fourth International Conference on. IEEE, 2007: 149-154.
[6] Lin L, Hongbing J. Signal feature extraction based on an improved EMD method[J]. Measurement, 2009, 42(5): 796-803.
[7] Huang N E, Shen Z, Long S R. A new view of nonlinear water waves: The Hilbert Spectrum 1[J]. Annual review of fluid mechanics, 1999, 31(1): 417-457.
[8] 江莉, 李林, 董惠. 基于改进 EMD 方法的多分量信号分析[J]. 振动与冲击, 2009, 28(4): 51-53.
JIANG Li, LI Lin, DONG Hui. An improved empirical mode decomposition method for multicomponent signal represntation [J]. Journal of vibration and shock, 2009, 28(4): 51-53.
[9] 郑天翔, 杨力华. 经验模式分解算法的探讨和改进[J]. 中山大学学报 (自然科学版), 2007, 46(1): 1-6.
ZHENG Tian-xiang, YANG Li-hua. Discussion and Improvement on Empirical Mode Decomposition Algorithm[J]. Journal of Zhongshan University (natural science edition) , 2007, 46(1): 1-6.
[10] Rilling G, Flandrin P. One or two frequencies?The empirical mode decomposition answers[J]. Signal Processing, IEEE Transactions on, 2008, 56(1): 85-95.