由于磁场无处不在的特点,使得磁场定位广泛应用于目标定位和状态检测中,然而在含有复杂铁磁质环境下,磁场信号的变化会导致定位精度下降甚至不能定位等问题.针对上述问题,提出了一种将磁场定位与BP神经网络相结合的方法,并进行了实验验证. 结果表明,基于BP神经网络的磁场定位方法可用于含有铁磁质的复杂环境定位. 定位精度与数据采集时磁源的移动步长、磁场传感器数量及传感器电子噪声有关,移动步长越小,传感器数量越多,电子噪声越小,定位精度越高.
The ubiquitous nature of magnetic fields makes magnetic field localization widely used in target localization and condition detection. However, in the environment containing complex ferromagnetic mass, the variation of the magnetic field signal can lead to problems such as degradation of localization accuracy or even failure to localize. To address these problems, a method combining magnetic field localization with BP neural network is proposed, and experimental verified. The results show that the BP neural network-based magnetic field localization method can be used for the localization of complex environments containing ferromagnetic materials. The localization accuracy is related to the movement step of the magnetic source, the number of magnetic field sensors and the electronic noise of the sensors during data acquisition. The smaller the movement step, the more the sensors and the smaller the electronic- DOI:10.3969/j.issn.1000-1565.2022.06.014基于神经网络的磁场定位技术王华英1, 2, 3,孙海军1,张雷1,2,3,王学1,2,3,黄艳宾1,2,3,郭海军1,2,3(1.河北工程大学 数理科学与工程学院,河北 邯郸 056038;2.河北省计算光学成像与光电检测技术创新中心,河北 邯郸 056038;3.河北省计算光学成像与智能感测国际联合研究中心,河北 邯郸 056038)摘 要:由于磁场无处不在的特点,使得磁场定位广泛应用于目标定位和状态检测中,然而在含有复杂铁磁质环境下,磁场信号的变化会导致定位精度下降甚至不能定位等问题.针对上述问题,提出了一种将磁场定位与BP神经网络相结合的方法,并进行了实验验证. 结果表明,基于BP神经网络的磁场定位方法可用于含有铁磁质的复杂环境定位. 定位精度与数据采集时磁源的移动步长、磁场传感器数量及传感器电子噪声有关,移动步长越小,传感器数量越多,电子噪声越小,定位精度越高.关键词:磁场;传感器;定位;BP神经网络;定位精度中图分类号:TP394.1 文献标志码:A 文章编号:1000-1565(2022)06-0657-08Research on localization of magnetic field based on neural networkWANG Huaying1,2,3, SUN Haijun1, ZHANG Lei1,2,3, WANG Xue1,2,3, HUANG Yanbin1,2,3, GUO Haijun1,2,3(1. College of Mathematical Science and Engineering, Hebei University of Engineering, Handan 056038, China; 2. Hebei Computational Optical Imaging and Photoelectric Detection Technology Innovation Center, Handan 056038, China; 3. Hebei International Joint Research Center for Computational Optical Imaging and Intelligent Sensing, Handan 056038, China)Abstract: The ubiquitous nature of magnetic fields makes magnetic field localization widely used in target localization and condition detection. However, in the environment containing complex ferromagnetic mass, the variation of the magnetic field signal can lead to problems such as degradation of localization accuracy or even failure to localize. To address these problems, a method combining magnetic field localization with BP neural network is proposed, and experimental verified. The results show that the BP neural network-based magnetic field localization method can be used for the localization of complex environments containing ferromagnetic materials. The localization accuracy is related to the movement step of the magnetic source, the number of magnetic field sensors and the electronic noise of the sensors during data acquisition. The smaller the movement step, the more the sensors and the smaller the electronic- 收稿日期:2022-03-28 基金项目:国家自然科学基金资助项目(62175059);河北省创新能力提升计划资助项目(20540302D);邯郸市科学技术与发展计划项目(21422111246;19422031008-4) 第一作者:王华英(1963—),女,河北涉县人,河北工程大学教授,博士,主要从事机器视觉方面研究.E-mail: pbxsyingzi@126.com 通信作者:郭海军(1967—),男,河北广平人,河北工程大学实验师,主要从事机器视觉方面研究.E-mail: ghj6028039@163.com第6期王华英等:基于神经网络的磁场定位技术noise, the higher the localization accuracy.
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