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兵工学报 ›› 2023, Vol. 44 ›› Issue (2): 526-533.doi: 10.12382/bgxb.2021.0740

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基于动态学习策略多群体粒子群的消磁站水下磁传感器位置校正方法

王玉芬, 周国华, 吴轲娜*(), 李林锋   

  1. 海军工程大学 电气工程学院, 湖北 武汉 430000
  • 收稿日期:2022-06-11 上线日期:2022-06-11
  • 通讯作者:
  • 基金资助:
    国家自然科学基金项目(51107145); 国家自然科学基金项目(51377165)

Underwater Magnetic Sensor Position Correction Method Based on Multi-Population Particle Swarm Optimization Using Dynamic Learning Strategies

WANG Yufen, ZHOU Guohua, WU Kena*(), LI Linfeng   

  1. School of Electrical Engineering, Naval University of Engineering, Wuhan 430000, Hubei, China
  • Received:2022-06-11 Online:2022-06-11

摘要:

消磁站海底敷设磁传感器是舰艇磁场测量的主要形式之一,水下磁传感器的位置偏差直接影响着舰艇磁场的测量精度和防护能力评估。针对现有方法难以准确定位消磁站水下磁传感器的问题,提出一种基于动态学习策略多群体粒子群的消磁站水下磁传感器位置校正方法。该方法首先将通电载流线圈等效成磁偶极子磁源,再通过线性多重计量方法改变磁源与磁传感器的相对位置以获取多组磁传感器磁场测量数据,据此建立水下磁传感器位置校正模型,并采用动态学习策略多群体粒子群优化算法优化求得位置偏差矢量,从而实现水下磁传感器位置的高精度校正。在综合分析磁偶极子等效误差等主要影响因素的基础上,设计了数值模拟实验和物理缩比模型实验,结果表明:该方法可有效解决消磁站水下磁传感器的位置校正问题,校正后x轴、y轴和z轴三个方向的位置误差均小于0.1m。经过校正后的消磁站磁场测量精度可以满足舰艇磁场测量要求,该方法可以对消磁站位置安装偏差不大于0.3m的水下磁传感器完成校正工作,具有较好的实用价值。

关键词: 水下磁传感器, 位置校正, 磁偶极子, 多群体粒子群

Abstract:

Laying magnetic sensors on the seabed of the magnetic deperming facility is one of the main ways to measure ships' magnetic field. The position deviation of underwater magnetic sensors directly affects the measurement accuracy and evaluation of protection ability of ships' magnetic field. To address the problem that the existing methods are difficult to accurately locate the underwater magnetic sensors of the deperming station, a position correction method of underwater magnetic sensors of the deperming station based on multi-population particle swarm optimization (PSO) using dynamic learning strategies is proposed. Firstly, the energized current-carrying coil is equivalent to a magnetic dipole magnetic source, and then the relative position between the magnetic source and the magnetic sensor is changed by the linear multi-measurement method to obtain the magnetic field measurement data of the multiple groups of magnetic sensors. Based on this, the position correction model of underwater magnetic sensors is established, and the position deviation vector is optimized by the multi-population PSO algorithm using dynamic learning strategies, thus realizing the high-precision correction of the position of the underwater magnetic sensors. Based on the comprehensive analysis of the main influencing factors such as the equivalent error of the magnetic dipole, the numerical simulation and physical scale model experiment are designed. The results show that: this method can effectively solve the problem of position correction of underwater magnetic sensors in the deperming station; after correction, the position errors in x,y and z directions are less than 0.1m; the magnetic field measurement accuracy of the deperming station after correction can meet the requirements of ships' magnetic field measurement. This method can complete the correction of the underwater magnetic sensors with a position deviation of no more than 0.3m, and has good practical value.

Key words: underwater magnetic sensors, position correction, magnetic dipole, multi-population particle swarm optimization

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