基于小波变换的大尺度岩体结构微震监测信号去噪方法研究  

A study on method of signal denoising based on wavelet transform for micro-seismicity monitoring in large-scale rockmass structures

作　　者：徐宏斌[1] 李庶林[1] 陈际经[2] 

机构地区：[1]厦门大学建筑与土木工程学院,福建厦门361005 [2]湖南柿竹园有色金属有限责任公司,湖南郴州423037

出　　处：《地震学报》2012年第1期85-96,127,共12页Acta Seismologica Sinica

基　　金：国家自然科学基金(10572122)资助

摘　　要：为将小波去噪方法应用于大尺度岩体结构微震监测信号的去噪研究,首先在MAT-LAB环境下进行仿真,验证了使用Symlet6小波进行小波去噪的可行性;利用4种自适应阈值规则对含噪信号进行去噪对比,结果表明4种阈值去噪后的信号在均方差较小的情况下都极大地提高了信号的信噪比,有效地去除了噪声,对不同的含噪信号,无偏似然原则阈值去噪后的信噪比最高,同时均方差也最小,在去噪时显得更为有效;以柿竹园全数字多通道微震监测系统为背景,将MATLAB仿真结论应用于现场微震信号的去噪研究,结果表明小波阈值去噪特别适合大尺度岩体微震信号这一类非稳定信号的去噪分析,既可以对低信噪比的微震信号提取出有效信号,也可以对频率覆盖范围广的微震信号在各尺度上提取并重构出有效信号,实现了对微震真实信号和噪声信号的有效分离.This paper applied wavelet denoising method to monitoring microseismieity in large-scale rockmass structure. The feasibility of using symlet6 in wavelet denoising was validated with MATLAB simulation. Then four types of adaptive threshold rules for wavelet denoising are used to denoise three noisy signals. The result shows that the noise in signals can be filtered effectively with the four threshold rules and the Rigrsure threshold for wavelet denoising is more effective with the least mean square deviation and ratio. Based on the multi-channel digital microseism highest signal to noise monitoring system in Shizhuyuan mine, this paper applied wavelet denoising method to three different microseismic signals with the result of MATLAB simulation. The results show that the true microseismic signals can be recovered from the noisy signals by removing noise at every wavelet scale, even though noisy signals have low signal to noise ratio or include wide frequency range. The wavelet threshold denoising is suited especially to the denoising of microseismic monitoring signals in largescale rockmass structures.

关 键 词：小波去噪 大尺度岩体 微震技术 MATLAB仿真 

分 类 号：P315.9[天文地球—地震学]