|
|
|
| Method of Eliminating Mode Mixing of Empirical Mode Decomposition with Intermittency Signal Based on AMD |
| SHI Pei-ming1,SU Cui-jiao1,HAN Dong-ying1,LIU Shuang2 |
1. Institute of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China
2. Science and Technology Research Institute, Yanshan University, Qinhuangdao, Hebei 066004, China |
|
|
|
|
Abstract Aiming at mode mixing of empirical mode decomposition (EMD) caused by the intermittency signal, a new method to eliminate mode mixing of EMD based on analytical mode decomposition, AMD, is proposed. In this method, taking advantage of instantaneous frequency characteristics of the first intrinsic mode function, IMF, the frequency components of IMF1 can be got, the bisecting frequency and the location of the intermittency signal. Then, AMD is used to extract the intermittency signal and decompose the processed signal by EMD method. Thus, the effect of the intermittency signal is eliminated. The results of simulation analysis and engineering application show that the proposed method can effectively eliminate mode mixing of EMD caused by intermittency signal.
|
|
Received: 30 October 2014
Published: 27 January 2016
|
|
|
|
Corresponding Authors:
pei-ming shi
E-mail: spm@ysu.edu.cn
|
|
|
|
［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［J］. Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 1998, 454(1971): 903-995.
［2］刘彬, 蒋金水, 于伟凯. EMD相关度去噪及其在轧机信号处理中的应用［J］. 计量学报, 2009, 30(1): 73-77.
［3］谢平, 王欢, 杜义浩. 基于EMD和Wigner-Ville分布的机械故障诊断方法研究［J］. 计量学报, 2010, 31(5): 390-394.
［4］时培明, 丁雪娟, 李庚,等. 一种 EMD 改进方法及其在旋转机械故障诊断中的应用［J］. 振动与冲击, 2013, 32(4):185-190.
［5］Shen W C, Chen Y H, Wu An-Yeu (Andy). Low-complexity sinusoidal-assisted EMD (SAEMD) algorithms for solving mode-mixing problems in HHT［J］. Digital Signal Processing, 2014, 24: 170-186.
［6］胡重庆, 李艾华. EMD 间歇信号的检测和提取方法［J］. 数据采集与处理, 2008, 23(1): 108-111.
［7］赵进平. 异常事件对 EMD 方法的影响及其解决方法研究［J］. 青岛海洋大学学报: 自然科学版, 2001, 31(6): 805-814.
［8］Zhang J, Yan R Q, Gao R, et al. Performance enhancement of ensemble empirical mode decomposition ［J］. Mechanical Systems and Signal Processing, 2010, 24(7): 2104-2123.
［9］汤宝平, 董绍江, 马靖华. 基于独立分量分析的 EMD 模态混叠消除方法研究［J］. 仪器仪表学报, 2012, 33(7): 1477-1482.
［10］赵玲, 刘小峰, 秦树人,等. 消除经验模态分解中混叠现象的改进掩膜信号法［J］. 振动与冲击, 2010, 29(9): 13-17.
［11］Chen G D, Wang Z C. A signal decomposition theorem with Hilbert transform and its application to narrowband time series with closely spaced frequency components［J］. Mechanical Systems and Signal Processing, 2012, 28（4）: 258-279.
［12］李苗, 任伟新, 胡异丁,等. 基于解析模态分解法的桥梁动态应变监测数据温度影响的分离［J］. 振动与冲击, 2012, 31(21): 6-10.
［13］Feldman M. A signal decomposition or lowpass filtering with Hilbert transform ［J］. Mechanical Systems and Signal Processing, 2011, 25(8): 3205-3208. |
|
|
|
2016, Vol. 37 
