地面核磁共振,包络提取,局部均值分解,信噪比,拟合误差 ," />

地面核磁共振,包络提取,局部均值分解,信噪比,拟合误差 ,"/> <p class="MsoPlainText"> 基于局部均值分解的地面核磁共振信号包络提取方法

吉林大学学报(地球科学版) ›› 2022, Vol. 52 ›› Issue (3): 766-774.doi: 10.13278/j.cnki.jjuese.20210245

• 第十五届中国国际地球电磁学术研讨会专栏 • 上一篇    下一篇

基于局部均值分解的地面核磁共振信号包络提取方法

田宝凤1, 2,孙士聪2,刘隆昌2,蒋川东1, 2   

  1. 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

  • 出版日期:2022-05-26 发布日期:2024-01-03
  • 基金资助:

    吉林省科技厅项目(20190201111JC);吉林省教育厅项目 (JJKH20211052KJ)


Extraction of Surface Nuclear Magnetic Resonance Signals Based on Local Mean Decomposition

Tian Baofeng1, 2, Sun Shicong2, Liu Longchang2, Jiang Chuandong1, 2   



  1. 1. Key Laboratory of Geophysical Exploration Equipment  (Jilin University), Ministry of Education, Changchun 130026, China

    2. College of Instrument Science and Electrical Engineering, Jilin University, Changchun 130026, China

  • Online:2022-05-26 Published:2024-01-03
  • Supported by:
    Supported by the Project of Science and Technology Department of Jilin Province (20190201111JC) and the Project of Education Department of Jilin Province (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30.3~37.2 dB。


关键词:

地面核磁共振')">

地面核磁共振, 包络提取, 局部均值分解, 信噪比, 拟合误差

Abstract:

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.

Key words:  , surface nuclear magnetic resonance, envelope extraction, local mean decomposition, signal-to-noise ratio, error of fitting ,

中图分类号: 

  • P631
[1] 陈毅军, 程浩, 巩恩普, 薛林. 基于Shearlet变换的尺度方向自适应阈值地震数据随机噪声压制方法[J]. 吉林大学学报(地球科学版), 2021, 51(4): 1231-1242.
[2] 张雪冰, 刘财, 刘洋, 王典, 勾福岩. 基于局部均值分解的地震信号时频分解方法[J]. 吉林大学学报(地球科学版), 2017, 47(5): 1562-1571.
[3] 习建军, 曾昭发, 黄玲, 崔丹丹, 王者江. 阵列式探地雷达信号极化场特征[J]. 吉林大学学报(地球科学版), 2017, 47(2): 633-644.
[4] 刘霞, 黄阳, 黄敬, 段志伟. 基于经验模态分解(EMD)的小波熵阈值地震信号去噪[J]. 吉林大学学报(地球科学版), 2016, 46(1): 262-269.
[5] 贾海青, 姜弢, 徐学纯, 葛利华, 林君, 杨志超. 可控震源记录中的脉冲噪声分析[J]. 吉林大学学报(地球科学版), 2015, 45(1): 302-311.
[6] 刘财, 崔芳姿, 刘洋, 王典, 刘殿秘, 张鹏. 基于低信噪比条件下新型Seislet变换的阈值去噪方法[J]. 吉林大学学报(地球科学版), 2015, 45(1): 293-301.
[7] 董烈乾, 李振春, 刘磊, 李志娜, 桑运云. 基于经验模态分解的曲波阈值去噪方法[J]. J4, 2012, 42(3): 838-844.
[8] 刘财, 冯智慧, 谢金娥, 冯晅, 王典. 基于四阶累积量的同相轴自动拾取方法[J]. J4, 2010, 40(5): 1188-1193.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!