一种舰船高精度感应磁场快速正演建模方法

doi:10.19595/j.cnki.1000-6753.tces.222204

摘要
图/表
参考文献
相关文章 (1)

全文: PDF (753 KB)
输出: BibTeX | EndNote (RIS)

摘要

为了解决矢量积分方程法计算舰船感应磁场时效率较低和计算量较大的问题,提出一种基于简化标量磁位的积分方程正演模型,并引入了多层自适应交叉近似 (multi-level adaptive cross approximation, MLACA)算法,不仅能够保证磁场计算精度,还能大幅减少计算机的内存需求和计算时间。数值仿真表明使用基于MLACA的标量积分方程法能够快速获取高精度的铁磁物体感应磁场。针对舰船铁磁材料的磁性参数不易获取的问题,基于磁场实测值和正演耦合模型,以磁场拟合度、磁化率先验分布和光滑约束条件为目标函数建立了磁化率反演模型,并采用模拟退火(simulated annealing, SA)算法优化得到了等效磁化率的空间分布。球壳数值仿真和船模试验结果表明,磁化率反演优化模型有效可行,其中球壳磁场的预测误差为2.2%,船模磁场的预测误差约为4.8%。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	何保委
	孙兆龙
	刘月林
	周国华
	唐烈峥

关键词 ：舰船磁场, 简化标量磁位, 多层自适应交叉近似, 模拟退火法, 等效磁化率

Abstract：

Mastering the distribution of a ship’s induced magnetic field is an important issue for implementing magnetic stealth technology, and the integral equation method is one of the main methods to calculate the ship’s induced magnetic field. Integral equation method only needs to discretize the ferromagnetic region and does not need to consider the boundary conditions, so it has been widely concerned and applied. The traditional vector integral equation for modeling induced magnetic fields has the problems of low efficiency and a large computational burden. Considering that there are many discrete elements of large ferromagnetic objects such as ships, the coupling coefficient between elements forms a huge asymmetric dense matrix, so the computing time and memory requirement will increase sharply with the increase of the number of elements. To address these issues, a scalar magnetic potential integral equation method based on surface elements is proposed, and multi-level adaptive cross approximation (MLACA) algorithm is introduced. Since the integral equation method needs to obtain the magnetic susceptibility of ferromagnetic materials, the equivalent magnetic susceptibility inversion model is established based on the forward algorithm.
Firstly, the scalar magnetic potential integral formula based on triangular surface elements is derived. According to the principle of linear interpolation, the scalar magnetic potential of the center point of discrete elements is expressed by interpolation function and node scalar magnetic potential, and the elements’ coupling coefficient matrix is obtained by establishing a local coordinate system. Therefore, the scalar integral method of surface elements for solving ship’s induced magnetic field is obtained. Secondly, to realize the modeling problem of the induced magnetic field of large ships, the MLACA algorithm is introduced, which not only guarantees the accuracy of magnetic field calculation but also greatly reduces the memory requirement and computing time of the computer. Finally, aiming at the problem that the magnetic parameters of ferromagnetic materials of ships are not easy to obtain, a magnetic susceptibility inversion model is established based on the measured magnetic field values and the forward coupling model, taking the magnetic field fitting degree, prior distribution of magnetic susceptibility and smooth constraint as the objective function. The spatial distribution of equivalent magnetic susceptibility has been optimized by simulated annealing (SA) algorithms.
A numerical simulation of the iron spherical shell shows that the proposed scalar magnetic potential coupling forward modeling method can obtain the ship’s induced magnetic field efficiently with high precision. For the same discrete elements, compared with the vector method, the scalar method can save about 97% of the memory consumption and 65% of the computing time, which verifies the effectiveness of the scalar magnetic potential integral equation method based on the MLACA algorithm. According to the inversion model, the equivalent magnetic susceptibility of the iron spherical shell is optimized by the SA algorithm, which is utilized to predict the spherical shell of other positions and the average relative error is only 2.2%. After using of smooth constraint condition, the equivalent magnetic susceptibility obtained is smoother.
In order to verify the practicability of the proposed forward modeling method and magnetic susceptibility inversion method in engineering, an experimental scheme was designed for a reduced-scale ship model with unknown magnetic parameters. Firstly, the equivalent magnetic susceptibility distribution of the ship model is obtained by measuring the magnetic field of the ship model at the z1 plane, and it is used to predict the induced magnetic field at the z2 plane. The magnetic field fitting error and prediction error of the ship are about 5.0%, indicating that the proposed forward modeling model of induced magnetic field and the inverse optimization model of equivalent magnetic susceptibility can be used for induced magnetic field modeling of large ships with high precision and can provide support for the implementation of magnetic stealth technology on ships.

Key words： Ship magnetic field reduced scalar magnetic potential multi-level adaptive approximate cross simulated annealing method equivalent magnetic susceptibility

收稿日期: 2022-11-22

PACS:

TM153

基金资助:

国家自然科学基金资助项目（51377165, 52207020）

通讯作者: 刘月林女,1989年生,硕士,讲师,研究方向为电磁环境与防护技术。E-mail：mooncake1024@163.com

作者简介: 何保委男,1995年生,博士生,研究方向为电磁环境与防护技术。E-mail：hebaowei188@163.com

引用本文:

何保委, 孙兆龙, 刘月林, 周国华, 唐烈峥. 一种舰船高精度感应磁场快速正演建模方法[J]. 电工技术学报, 0, (): 129-129. He Baowei, Sun Zhaolong, Liu Yuelin, Zhou Guohua, Tang Liezheng. A Fast Forward Modeling Method for High Precision Induced Magnetic Field of Ships. Transactions of China Electrotechnical Society, 0, (): 129-129.

链接本文:

https://dgjsxb.ces-transaction.com/CN/10.19595/j.cnki.1000-6753.tces.222204 https://dgjsxb.ces-transaction.com/CN/Y0/V/I/129

[1] Holmes J J.Reduction of a ship’s magnetic field signatures[M]. Maryland, USA: Morgan & Claypool Publishers, 2008.
[2] 刘大明. 舰船消磁理论与方法[M]. 北京: 国防工业出版社, 2011.
[3] 郭成豹, 殷琦琦. 舰船磁场磁单极子阵列法建模技术[J]. 物理学报, 2019, 68(11): 106-115.
Guo Chengbao, Yin Qiqi.Magnetic monopole array model for modeling ship magnetic signatures[J]. Acta Physica Sinica, 2019, 68(11): 106-115.
[4] 戴忠华, 周穗华, 张晓兵. 多目标优化的舰船磁场建模方法[J]. 物理学报, 2021, 70(16): 147-159.
Dai Zhonghua, Zhou Suihua, Zhang Xiaobing.Multi-objective optimization of ship magnetic field modeling method[J]. Acta Physica Sinica, 2021, 70(16): 147-159.
[5] 刘琪, 孙兆龙, 姜润翔, 等. 一种舰船下方磁场的信号重构及换算方法[J]. 电工技术学报, 2022, 37(15): 3723-3732.
Liu Qi, Sun Zhaolong, Jiang Runxiang, et al.A signal reconstruction and conversion method of magnetic field under ship[J]. Transactions of China Electrotechnical Society, 2022, 37(15): 3723-3732.
[6] 刘芙妍, 颜冰. 磁偶极子阵列模型的适用性研究与优化分析[J]. 物理学报, 2022, 71(12): 36-48.
Liu Fuyan, Yan Bing.Applicability and optimization analysis of magnetic dipole array model[J]. Acta Physica Sinica, 2022, 71(12): 36-48.
[7] 徐庆林, 王向军, 张建春, 等. 921A钢板腐蚀电场的Frumkin修正[J].电工技术学报, 2020, 35(14): 2951-2958.
Xu Qinglin, Wang Xiangjun, Zhang Jianchun, et al.Frumkin correction of corrosion electric field generated by 921A steel[J]. Transactions of China Electrotechnical Society, 2020, 35(14): 2951-2958.
[8] 饶凡, 吴旭升, 高嵬, 等. 两极永磁电机静态内外磁场研究[J].电工技术学报, 2021, 36(14): 2936-2944.
Rao Fan, Wu Xusheng, Gao Wei, et al.Study on internal and external magnetic field of static two-pole permanent magnet motor[J]. Transactions of China Electrotechnical Society, 2021, 36(14): 2936-2944.
[9] Chadebec O, Coulomb J L, Janet F.A review of magnetostatic moment method[J]. IEEE Transactions on Magnetics, 2006, 42(4): 515-520.
[10] Fan M W, Shao H G, Wang J G.Some experiences of using integral equation method to calculate magnetostatic fields[J]. IEEE Transactions on Magnetics, 2006, 21(6): 2185-2187.
[11] 倪振群, 翁雪祥, 翁行泰. 舰船主甲板模型感应磁场的计算[J]. 上海交通大学学报, 1996, 30(7): 86-91.
Ni Zhenqun, Weng Xuexiang, Weng Xingtai.Computation of inductive magnetic field induced by vessel’s main deck model[J]. Journal of Shanghai Jiaotong University, 1996, 30(7): 86-91.
[12] 周国华, 肖昌汉, 刘胜道, 等. 基于六面体单元表面磁场积分法求解三维静磁场[J]. 电工技术学报, 2009, 24(3): 1-7.
Zhou Guohua, Xiao Changhan, Liu Shengdao, et al.3D magnetostatic field computation with hexahedral surface integral equation method[J]. Transactions of China Electrotechnical Society, 2009, 24(3): 1-7.
[13] 郭成豹, 刘大明. 薄钢壳物体磁特征建模研究[J]. 兵工学报, 2012, 33(8): 912-915.
Guo Chengbao, Liu Daming.Modeling of magnetic signatures of thin-sheet object[J]. Acta Armamentarii, 2012, 33(8): 912-915.
[14] 朱武兵, 庄劲武, 赵文春, 等. 载体感应磁场的改进积分方程法[J]. 国防科技大学学报, 2018, 40(3): 101-106.
Zhu Wubing, Zhuang Jinwu, Zhao Wenchun, et al.Modified integral equation method for carrier’s induced magnetic field solving[J]. Journal of National University of Defense Technology, 2018, 40(3): 101-106.
[15] 何保委, 周国华, 刘胜道, 等. 标量磁位积分方程法计算舰艇三维静磁场[J/OL]. 兵工学报, 2022. http://kns.cnki.net/kcms/detail/11.2176.TJ.20221027.1405.004.html
He Baowei, Zhou Guohua, Liu Shengdao, et al.Ship’s 3D magnetostatic field computation utilizing integral equation method of scalar magnetic potential[J]. Acta Armamentarii, 2022. Ship’s 3D magnetostatic field computation utilizing integral equation method of scalar magnetic potential[J]. Acta Armamentarii, 2022. http://kns.cnki.net/kcms/detail/11.2176.TJ.20221027.1405.004.html
[16] 郭成豹, 张晓锋, 肖昌汉, 等. 薄钢板船舶磁性的物理模型和数值模拟混合建模[J]. 哈尔滨工程大学学报, 2008, 29(3): 247-250.
Guo Chengbao, Zhang Xiaofeng, Xiao Changhan, et al.Magnetization determination of ships made of thin steel sheets by combining the physical model and numerical calculations[J]. Journal of Harbin Engineering Universit, 2008, 29(3): 247-250.
[17] 周国华, 肖昌汉, 闫辉, 等. 一种弱磁作用下铁磁物体感应磁场的计算方法[J]. 哈尔滨工程大学学报, 2009, 30(1): 91-95.
Zhou Guohua, Xiao Changhan, Yan Hui, et al.A method to calculate the induced magnetic field of ferromagnetic objects in a weak magnetic field[J]. Journal of Harbin Engineering Universit, 2009, 30(1): 91-95.
[18] Trowbridge C W.Progress in magnet design by computer[C]//Proceedings of 4th Conference Magnetostatic Technology, NewYork, USA, 1972: 555-565.
[19] Chadebec O.Modelling of magnetic field induced by shells-identification of the magnetisation application to the closed loop degaussing of a ferromagnetic hull[D]. Grenoble, France: Institut National Polytechnique de Grenoble, 2001.
[20] Guerin S.Magnetic source identification measurement robustness and optimization-application to ship magnetization reconstruction[D]. Grenoble, France: Institut National Polytechnique de Grenoble, 2005.
[21] Vuillermet Y.Closed loop degaussing applied to double hull submarine Magnetization identification from near magnetic field measurements[D]. Grenoble, France: Institut National Polytechnique de Grenoble, 2008
[22] Van L V.Developement of magnetostatic volume integral formulations[D]. Grenoble, France: Universite Grenoble Alpes, 2015.
[23] Chavin-Collin G, Bannwarth B, Cavallera D, et al.An integral face formulation for thin non-conductive magnetic regions[J]. IEEE Transactions on Magnetics, 2019, 55(6): 7000504.
[24] Chavin-Collin G.Identification de l’aimantation de tôles ferromagnétiques soumises à des champs magnétiques faibles et à de fortes contraintes mécaniques: application à l’immunisation magnétique des sous-marins en boucle fermée[D]. Grenoble, France: Universite Grenoble Alpes, 2020.
[25] 谢德馨, 杨仕友. 工程电磁场数值分析与优化设计[M]. 北京: 机械工业出版社, 2017.
[26] Van L V, Bannwarth B, Carpentier A, et al.The adaptive cross approximation technique for a volume integral equation method applied to nonlinear magnetostatic problems[J]. IEEE Transactions on Magnetics, 2014, 50(2): 7010904.
[27] 周耀忠, 张国友. 舰船磁场分析计算[M]. 北京: 国防工业出版社, 2004.
[28] 陈杰, 鲁习文. 舰船感应磁场预测的一种新方法[J]. 物理学报, 2010, 59(1): 239-245.
Chen Jie, Lu Xiwen.A new method for predicting the induced magnetic field of naval vessels[J]. Acta Physica Sinica, 2010, 59(1): 239-245.
[29] 裴亚杰. 电磁场积分方程自适应交叉近似算法的研究[D]. 南京: 南京邮电大学, 2011.
[30] Vijn A R P J. Development of a closed-loop degaussing system towards magnetic unobservable vessels[D]. Delft, Netherlands: Delft University of Technology, 2021.
[31] 何保委, 刘胜道, 周国华, 等. 基于多目标模拟退火法的垂向检测线圈改进[J]. 华中科技大学学报(自然科学版), 2021, 49(12): 46-50.
He Baowei, Liu Shengdao, Zhou Guohua, et al.Improvement of vertical detecting coil based on multi-objective simulated annealing method[J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2021, 49(12): 46-50.
[32] 陈龙, 易琼洋, 贲彤, 等. 全局优化算法在Preisach磁滞模型参数辨识问题中的应用与性能对比[J]. 电工技术学报, 2021, 36(12): 2585-2593+2606.
Chen Long, Yi Qiongyang, Ben Tong, et al. Application and performance comparison of global optimization algorithms in the parameter identification problems of the Preisach hysteresis model[J]. Transactions of China Electrotechnical Society, 2021, 36(12): 2585-2593+2606.