基于标准差中位数的磁共振信号尖峰去除方法

吉林大学学报(信息科学版) ›› 2015, Vol. 33 ›› Issue (3): 241-245.

基于标准差中位数的磁共振信号尖峰去除方法

李同^a,b, 林昊^a,b, 田宝凤^a,b, 林君^a,b

吉林大学 a. 仪器科学与电气工程学院; b. 地球信息探测仪器教育部重点实验室, 长春 130026

收稿日期:2014-12-25 出版日期:2015-05-23 发布日期:2015-07-25
作者简介:李同(1986—), 男, 长春人, 吉林大学博士研究生, 从事核磁共振弱信号检测技术研究, （Tel）86-13944837151（E-mail）ltong1229@qq.com；林君（1954—）, 男, 吉林榆树人, 吉林大学教授, 博士生导师, 主要从事地球物理探测技术及仪器和虚拟仪器研究, （Tel）86-13019100118（E-mail）lin_jun@jlu.edu.cn。
基金资助:
国家自然科学基金资助项目（D040901）

Peak Interference Filtering Method for Surface Nuclear Magnetic Resonance Signals Based on Median of Standard Deviation

LI Tong^a,b, LIN Hao^a,b, TIAN Baofeng^a,b, LIN Jun^a,b

a. College of Instrumentation and Electrical Engineering; b. Key Laboratory of GeoExploration Instrumentation, Ministry of Education, Jilin University, Changchun 130026, China

Received:2014-12-25 Online:2015-05-23 Published:2015-07-25

摘要/Abstract

摘要：

针对核磁共振探测(SNMR: Surface Nuclear Magnetic Resonance）信号因受尖峰噪声干扰严重而导致其衰减形态被破坏的问题, 提出了基于标准差中位数的尖峰噪声筛选剔除方法。通过对重复采集的数据进行阈值设定, 准确识别并剔除信号中混入的随机性强、幅值高的尖峰干扰。仿真实测结果表明, 该方法能有效去除大于信号幅值10倍的多处尖峰噪声, 同时能较好地还原真实信号的衰减形态。

关键词: 核磁共振, 尖峰噪声, 标准差, 中位数

Abstract:

Signals reliability of SNMR(Surface Nuclear Magnetic Resonance) is seriously influenced spiky noise caused by operating engineering machinery, in order to solve the problem an algorithm based on the median of standard deviation is developed and operated on artificial SNMR signals. This technique is designed to conduct threshold comparison to recognize and delete those spiky noise of strong randomness and high amplitude. By operating this method on artificial and field SNMR signals, it can be found that many spiky noise with amplitude of 10 times larger than real SNMR signal are removed. The decay shape of real SNMR signal are well restored.

Key words: surface nuclear magnetic resonance(SNMR), peak interference, standard deviation, median

中图分类号:

TN911.72

李同, 林昊, 田宝凤, 林君. 基于标准差中位数的磁共振信号尖峰去除方法[J]. 吉林大学学报(信息科学版), 2015, 33(3): 241-245.

LI Tong, LIN Hao, TIAN Baofeng, LIN Jun. Peak Interference Filtering Method for Surface Nuclear Magnetic Resonance Signals Based on Median of Standard Deviation[J]. Journal of Jilin University(Information Science Ed, 2015, 33(3): 241-245.

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