经验小波变换在信号趋势项提取中的应用研究  

Application of empirical wavelet transform for signal trend extraction

作　　者：张军[1] 郑玉新 赵静[1] Zhang Jun;Zheng Yuxin;Zhao Jing(Baicheng ordnance test center, Baicheng 137001, China)

机构地区：[1]白城兵器试验中心

出　　处：《电子测量技术》2019年第16期17-22,共6页Electronic Measurement Technology

摘　　要：经验小波变换(EWT)是一种新的自适应信号分解方法,它能将信号分解成不同的纯调幅-调频(AM-FM)分量。基于上述性质提出了一种新的信号趋势项提取方法,通过排除信号分解分量中的AM-FM成分提取出信号中的趋势分量。仿真结果表明,经验小波变换趋势项提取方法与EMD方法相比有一定的优势,为趋势项提取提供了一种新的有效方法。最后将该方法应用于实测振动位移信号趋势项提取中,结果进一步证明了提出方法的有效性,与EMD方法相比能够更真实地提取出信号趋势分量。Empirical wavelet transform (EWT) is a new self adaptive signal decomposition method. This method decomposes signal into different pure AM-FM component. A new signal trend extraction method, which extracted the trend component from the signal by removing the AM-FM signal component of the decomposed signal components, is proposed based on the above properties. The simulation results show that the trend extraction method based on EWT is superior to the EMD method, and provides a new and effective method for trend extraction. Finally, the proposed method was successfully applied to trend extraction of the actual measured vibration displacement signal. The results show that the proposed method is effective, and can effectively extracted trend component from the signal compared to the EMD method.

关 键 词：信息处理技术 经验小波变换 趋势项 经验模态分解 

分 类 号：TN911.7[电子电信—通信与信息系统]