噪声干扰环境下抑制EMD模态混叠方法  

Resolving the Mode-mixing Problem of EMD in the Presence of Noise

作　　者：黎恒[1] 李智[2,3] 莫玮[1] 张绍荣[2] 

机构地区：[1]西安电子科技大学机电工程学院,陕西西安710071 [2]桂林航天工业学院自动化系,广西桂林541004 [3]桂林电子科技大学电子工程与自动化学院,广西桂林541004

出　　处：《信号处理》2015年第8期956-961,共6页Journal of Signal Processing

基　　金：桂林航天工业学院基金项目(YJ1402)

摘　　要：经验模态分解(EMD)作为时频分析的经典算法,已经得到广泛的应用。然而,其分解质量容易受到噪声等干扰的影响,产生模态混叠问题。本文针对经验模态分解中因噪声存在的模态混叠问题,提出一种自适应的预处理方法。首先对输入信号进行B样条最小二乘拟合,消除了噪声的影响后,再进行EMD分解。为提高算法的自适应性,提出了一种基于极值点出现时刻的节点选取方法。对线性信号与非线性信号的仿真实验表明该方法有较高的分解精度;与聚合经验模态分解方法(EEMD)的分析对比结果表明该方法能很好地抑制噪声引起的模态混叠。Empirical mode decomposition has become an established tool for time-frequency analysis and has been widely used. However, a major problem is that its performance of EMD may be affected by intermittence or noise, known as the mode-mixing problem. In order to overcome the mode-mixing problem in the empirical mode decomposition （EMD） algo- rithm, an adaptive pre-processing technique is proposed. In this work, B-spline least squares approximation is first studied and employed before the use of EMD to eliminate the noise which may result in mode mixing. After that, a knot placement iteration algorithm using the extrema time location is put forward to enhance the adaptive property of the proposed method. Simulations of linear and non-linear signals show that it is capable of significantly reducing mode-mixing problem caused by noise. Comparisons between the proposed method and EEMD method are carried out, indicating that the proposed method is superior to existing methods in accuracy.

关 键 词：经验模态分解 模态混叠 B样条拟合 时频分析 信号分解 

分 类 号：TN911.72[电子电信—通信与信息系统]