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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
引用本文:徐宏斌,李庶林,陈际经. 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[J]. 地震学报, 2012, 34(1): 85-96
作者姓名:徐宏斌  李庶林  陈际经
作者单位:1) 中国福建厦门361005厦门大学建筑与土木工程学院 2) 中国湖南郴州 423037 湖南柿竹园有色金属有限责任公司
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MATLAB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...

关 键 词:小波去噪  大尺度岩体  微震技术  MATLAB仿真

A study on method of signal denoising based on wavelet transform for micro-seismicity monitoring in large-scale rockmass structures
Xu Hongbin , Li Shulin , Chen Jijing. A study on method of signal denoising based on wavelet transform for micro-seismicity monitoring in large-scale rockmass structures[J]. Acta Seismologica Sinica, 2012, 34(1): 85-96
Authors:Xu Hongbin    Li Shulin    Chen Jijing
Affiliation:1)School of Architecture and Civil Engineering of Xiamen University, Fujan, Xiamen 361005, China2)Hunan Shizhuyuan Nonferrous Metals Company Limited, Hunan, Chenzhou 423037, China
Abstract:This paper applied wavelet denoising method to monitoring micro-seismicity 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 highest signal to noise ratio.Based on the multi-channel digital microseism 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 large-scale rockmass structures.
Keywords:wavelet de-noising  large-scale rockmass  microseismic technology  MATLAB simulation
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