摘要
基于经验模态分解(EMD)、小波法、最小二乘法分别研究了爆破震动测试信号中趋势项的去除算法,并对三种方法去除趋势项效果及重构信号的时频特征进行对比分析。研究表明:小波法、最小二乘法去除测试信号趋势项时需预先设置先验的分解函数基,而EMD法在处理具有短时非平稳特性的爆破震动信号时具有自适应性,因此工程爆破震动测试信号预处理分析中采用EMD法能够更为有效地消除趋势项,提高信号时域和频域分辨率,对准确提取爆破震动时频特征具有重要参考价值。
The trend removing algorithm of blasting vibration monitoring signals were studied,based on empirical mode decomposition（EMD）,wavelet transform,and the least square method.Effects of trend removing by the three methods were compared and the time-frequency feature of reconstructed signals were analyzed.The study indicates that wavelet and least square methods need a predefine decomposition function basis in the trend removing of monitoring signals.EMD is adaptive,more practical and flexible in processing blasting vibration signals which are short and nonstationary.Thusly,the EMD method can remove trend more effectively and improve the resolution of a time-frequency domain in the preprocessing analysis of blasting vibration monitoring signals.It has an important reference value for the extracting time-frequency feature of blasting vibration signals accurately.
出处
《工程力学》
EI
CSCD
北大核心
2012年第10期63-68,共6页
Engineering Mechanics
基金
国家自然科学基金项目(51178460)
解放军理工大学预研基金项目(20110305)
关键词
爆破震动
趋势项
经验模态分解
最小二乘法
小波法
blasting vibration
trend
empirical mode decomposition
least square method
wavelet transform
