首页 | 本学科首页   官方微博 | 高级检索  
     检索      

磁记忆梯度张量测量信号预处理方法
引用本文:陈海龙,王长龙,左宪章,朱红运.磁记忆梯度张量测量信号预处理方法[J].系统工程与电子技术,2017,39(3):488-493.
作者姓名:陈海龙  王长龙  左宪章  朱红运
作者单位:军械工程学院无人机工程系, 河北 石家庄 050003
摘    要:为降低磁记忆测量信号中各种噪声干扰,提高磁记忆信号梯度张量解算精度,提出形态滤波和经验模态分解组合的方法消除噪声。首先,根据矢量合成原理将磁分量信号转换成总场幅值和方向信号,保证降噪处理过程中不改变各磁分量之间的内在关系;然后,利用形态滤波器对幅值和方向信号进行处理,消除信号中的瞬时强脉冲噪声;最后,将信号进行经验模态分解降噪,消除低频和局部干扰噪声。将上述方法用于磁记忆实测信号处理,结果表明,提出的方法能有效消除磁分量信号不同类型干扰噪声,解算得到高精度的磁记忆梯度张量数据。


Metal magnetic memory gradient tensor signal processing method
CHEN Hailong,WANG Changlong,ZUO Xianzhang,ZHU Hongyun.Metal magnetic memory gradient tensor signal processing method[J].System Engineering and Electronics,2017,39(3):488-493.
Authors:CHEN Hailong  WANG Changlong  ZUO Xianzhang  ZHU Hongyun
Institution:Department of Unmanned Aerial Vehicles Engineering, Ordnance Engineering College, Shijiazhuang 050003, China
Abstract:In order to improve the precision of metal magnetic memory (MMM) gradient tensor data, a method that combines the morphological filter and empirical mode decomposition(EMD) is proposed. To preserve the inter relation information between different magnetic field components while removing the noises, the data of magnetic field component is transformed into magnetic total-field strength and direction firstly. Then the data of magnetic field strength and direction is processed by the morphological filter to eliminate the influence of the instantaneous strong pulse. Finally, the processed data is decomposed with EMD to eliminate the influence of stochastic noise. An experiment on the actually acquired data is carried out to verify the proposed method, and the result shows that this method can effectively eliminate the noises in magnetic field components measurement signals and receive high precision data of magnetic memory gradient tensor.
Keywords:
点击此处可从《系统工程与电子技术》浏览原始摘要信息
点击此处可从《系统工程与电子技术》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号