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

doi:10.12382/bgxb.2021.0740

Abstract

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

CLC Number:

P229

WANG Yufen, ZHOU Guohua, WU Kena, LI Linfeng. Underwater Magnetic Sensor Position Correction Method Based on Multi-Population Particle Swarm Optimization Using Dynamic Learning Strategies[J]. Acta Armamentarii, 2023, 44(2): 526-533.

Figures/Tables 14

Fig.1 Geometric diagram of a submarine's physical model

Fig.2 Comparison of magnetic field under the keel

Table 1 Simulation results of sensor position deviation

序号	位置偏差幅值/m	最大绝对误差/nT
1	0.1	43
2	0.2	59
3	0.3	87
4	0.4	100

Fig.3 Schematic diagram of position correction

Fig.4 Diagram of magnetic field calculation of current-carrying coil

Fig.5 Dynamic learning mechanism scheme

Fig.6 Schematic diagram of simulation model

Fig.7 Equivalent error analysis of magnetic dipole

Fig.8 Analysis of sensor measurement accuracy error

Fig.9 Analysis of ambient noise error in sensor measurement

Table 2 Simulation results of sensor position correction

序号	偏差矢量/m	x轴方向/m	y轴方向/m	z轴方向/m
1	0.3,0,0	0.016	0.009	0.037
2	0,0.3,0	0.020	0.009	0.024
3	0,0,0.3	0.021	0.029	0.021
4	0.3,0.3,0.3	0.022	0.011	0.057
5	-0.3,0.3,0.3	0.021	0.011	0.058
6	0.3,-0.3,0.3	0.016	0.019	0.055
7	0.3,0.3,-0.3	0.018	0.009	0.044
8	-0.3,-0.3,-0.3	0.010	0.007	0.027

Fig.10 Layout of model experiment

Fig.11 Experimental results

Table 3 Model's experimental results

序号	偏差矢量/m	x轴方向/m	y轴方向/m	z轴方向/m
1	0.1, 0.1, 0.1	0.0032	0.0044	0.0090
2	-0.1, 0.1, 0.1	0.0051	0.0010	0.0064
3	0.1, -0.1, 0.1	0.0034	0.0081	0.0104
4	0.1, 0.1, -0.1	0.0037	0.0034	0.0053
5	-0.1, -0.1, -0.1	0.0078	0.0069	0.0116

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