基于STA/LTA改进的CEEMD-SVD微震信号降噪算法

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振动与冲击 ›› 2023, Vol. 42 ›› Issue (5) : 113-121.

论文

史艳楠1,2,3，齐朋磊1，王裕1，王毅颖1,2，张冲冲1

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Micro-seismic signal denoising algorithm based on CEEMD-SVD and STA/LTA

SHI Yannan1,2,3, QI Penglei1, WANG Yu1, WANG Yiying1,2, ZHANG Chongchong1

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文章历史 +

摘要

针对煤矿井下工作环境复杂，采集到的微震信号包含大量噪声信号，严重影响对微震信号的拾取、定位和反演。本文采用互补集合经验模态分解（CEEMD）联合奇异值分解（SVD）与长短时窗法（STA/LTA）相结合的降噪算法。利用CEEMD分解微震信号，得到固有模态分量（IMF），依据相关系数确定噪声主导的IMF和信号主导的IMF，通过STA/LTA去除CEEMD产生的伪分量。对噪声主导的分量进行SVD分解降噪后与信号主导的分量及剩余分量重构得到降噪后信号。加入模拟噪声信号与实际采集的微震信号进行仿真实验，结果表明本文算法在保证小剩余噪声干扰的情况下，可以节省计算时间。通过与经验模态分解（EMD）、聚合经验模态分解（EEMD）及新型自适应聚合经验模态分解（NAEEMD）降噪方法进行对比，依据信噪比、能量百分比及标准差三个评价指标进行定量计算，实验表明本文方法具有更好的降噪效果。

Abstract

In view of the complex working environment of underground coal mine, the collected microseismic signals contain a large number of noise signals, which seriously affects the pickup, location and inversion of microseismic signals. In this paper, complementary set empirical mode decomposition (CEEMD) combined with singular value decomposition (SVD) and STA/LTA are used to reduce noise. The microseismic signals were decomposed by CEEMD to obtain the inherent modal component (IMF) of the signals. The noise-dominated IMF and signal-dominated IMF were determined according to the correlation coefficient, and the pseudo-components generated by CEEMD were removed by STA/LTA. The denoised signal is obtained by SVD decomposition of noise-dominated IMF and reconstruction of signal-dominated IMF and residual components. The simulation results show that the proposed algorithm can save the computation time under the condition of small residual noise. Compared with empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD) and novel adaptive ensemble empirical mode decomposition (NAEEMD) denoising methods, the three evaluation indexes of SNR, energy percentage and standard deviation are calculated quantitatively, and the results show that the proposed method has better denoising effect.

导出引用

史艳楠1,2,3，齐朋磊1，王裕1，王毅颖1,2，张冲冲1. 基于STA/LTA改进的CEEMD-SVD微震信号降噪算法[J]. 振动与冲击, 2023, 42(5): 113-121

SHI Yannan1,2,3, QI Penglei1, WANG Yu1, WANG Yiying1,2, ZHANG Chongchong1. Micro-seismic signal denoising algorithm based on CEEMD-SVD and STA/LTA[J]. Journal of Vibration and Shock, 2023, 42(5): 113-121

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