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作 者:田宝凤[1,2] 孙士聪 刘隆昌 蒋川东[1,2] Tian Baofeng;Sun Shicong;Liu Longchang;Jiang Chuandong(Key Laboratory of Geophysical Exploration Equipment(Jilin University),Ministry of Education,Changchun130026,China;College of Instrument Science and Electrical Engineering,Jilin University,Changchun130026,China)
机构地区:[1]地球信息探测仪器教育部重点实验室(吉林大学),长春130026 [2]吉林大学仪器科学与电气工程学院,长春130026
出 处:《吉林大学学报(地球科学版)》2022年第3期766-774,共9页Journal of Jilin University:Earth Science Edition
基 金:吉林省科技厅项目(20190201111JC);吉林省教育厅项目(JJKH20211052KJ)。
摘 要:地面核磁共振(surface nuclear magnetic resonance,SNMR)技术由于其直接、定量、高效探测等优势在水文环境调查、预警灾害水源等领域中有着广泛应用.但在实际应用中,纳伏级别的SNMR信号往往淹没在复杂的环境噪声中难以分离,导致反演出的结果准确度降低.针对这一问题,本文提出了一种基于局部均值分解(local mean decomposition,LMD)的SNMR信号包络提取方法.首先,对含噪SNMR信号的实部包络与虚部包络从高频到低频依次进行分解;进而去除信号中的噪声干扰,提取所需的信号成分;最后合成有效的实部分量与虚部分量获得目标SNMR信号包络.结果表明:LMD算法提取SNMR信号包络获得初始振幅的拟合误差在±4.17%之内,平均横向弛豫时间拟合误差在±5.63%以内,信噪比提高了30.3~37.2dB.Because of the advantages of surface nuclear magnetic resonance,such as direct,quantitative and unique inversion,it is widely used in hydrological environment investigation,early warning of disaster water source,and other fields.However,in practical applications,the nanovolt level SNMR signals is often submerged in the environmental noise and difficult to break down,which makes the result inaccurate.In this paper,a method for extracting SNMR signal envelopes based on local mean decomposition(LMD)is proposed.First,the real and imaginary envelopes of the noisy SNMR signal are decomposed sequentially from high frequency to low frequency.Then the noise interferences in the signal are removed,and the required signal components are extracted.Finally,the effective real and imaginary components are synthesized to obtain the target SNMR signal envelope.The results indicate that the fitting error of the initial amplitude of the SNMR signal envelope extracted by LMD is within±4.17%,and the error of the average transverse relaxation time is within±5.63%.The signal-to-noise ratio is improved by 30.3-37.2 dB.
关 键 词:地面核磁共振 包络提取 局部均值分解 信噪比 拟合误差
分 类 号:P631[天文地球—地质矿产勘探]
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