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.
出处
《工程勘察》
CSCD
北大核心
2009年第7期67-71,共5页
Geotechnical Investigation & Surveying
关键词
经验模式分解
小波分解
GPS
变形分析
empirical mode decomposition
wavelet decomposition
GPS
deformation analysis
