爆破振动信号微分经验模态分解与经验模态分解对比分析

Comparision between differential empirical mode decomposition and empirical mode decomposition of blasting vibration signals

摘要: 本文介绍了一种爆破振动信号处理方法——微分经验模态分解(DEMD)，并结合多宝山铜矿选矿厂中碎车间基础爆破振动监测试验，与经验模态分解(EMD)进行对比分析爆破振动信号的频率筛分、混叠失真情况以及分解后信号的功率谱特性。结果显示：与EMD相比，DEMD有效地抑制了信号混叠失真现象，且从信号的功率谱变化特征得出DEMD将不同的优势频率分量提取出来，爆破振动信号频率筛分效果优越于EMD。

Abstract: A new analysis method of blasting vibration signals namely differential integral empirical mode decomposition(DEMD) is proposed.The comprehension of frequency sieving, aliasing distortion and the power spectrum characteristic of decomposition signals is explored combining with blasting vibration monitoring experiment by EMD and DEMD.The results show that aliasing distortion is controlled and different frequency components are extracted from the power spectrum of the signals by DEMD compared with EMD method.The conclusion indicates that DEMD is superior than EMD method at certain aspects.