经验模式分解与小波分解在变形分析应用中的对比分析  

Comparison of empirical mode decomposition and wavelet decomposition in deformation analysis

作　　者：李旋[1] 周清锋[1] 戴吾蛟[2] 杨礼平[1] 何伟[1] 

机构地区：[1]江苏省地质调查研究院,南京210018 [2]中南大学测绘与国土信息工程系,长沙410083

出　　处：《工程勘察》2009年第7期67-71,共5页Geotechnical Investigation & Surveying

摘　　要：经验模式分解和小波分解是当前有效处理非平稳信号的两种时频分析方法,它们各具有其优缺点,适用于不同的应用。信号突变性检测、趋势检测和频率检测的对比实验表明,在突变检测方面小波分解优于经验模式分解;但经验模式分解在低频信号检测及趋势检测方面优于小波分解,从对实际GPS动态位移监测分析的结果可以看出,经验模式分解更有利于缓慢变形趋势的提取和无噪声干扰下的低频变形信号检测。Wavelet decomposition （WD） and empirical mode decomposition （EMD） are two new time-frequency analytic methods to analyze the non-stationary signal. Simulated experiments of signal mutation signal trend extraction and frequency detection have demonstrated that both methods have their own characteristics in non- stationary signal processing. The results of these experiments show that WD should be better than EMD in signal mutation detection, while EMD is better than WD in low frequency signal detection and signal trend extraction. From the analysis of real GPS deformation monitoring measurements, it can be concluded that the EMD approach should be a promising tool for deformation trend extraction and low frequency deformation detection in low noise environment.

关 键 词：经验模式分解 小波分解 GPS 变形分析 

分 类 号：P228.4[天文地球—大地测量学与测量工程]