Underwater magnetic field measurement error compensation based on improved mayfly algorithm

基于改进蜉蝣算法的水下磁场测量误差补偿

School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China

Received: 18 November 2021

Abstract

This paper investigates the magnetic filed interference problem when the ROV equipped with a three-axis magnetometer measures the magnetic field of underwater magnetic targets within a short range, and a magnetic field compensation method based on an improved mayfly algorithm is proposed to improve the measurement accuracy of underwater magnetic field information. Firstly, a compensation model is established based on the installation error of the three-axis magnetometer and the interference magnetic field of the ROV. Then, in view of the problem that the original mayfly algorithm is easy to fall into local optimal and the convergence accuracy is poor, the Tent chaotic sequence and the Levy flight mutation strategy are introduced to improve the original mayfly algorithm. Finally, a series of magnetic field information is obtained through the three-axis magnetometer, and the original mayfly algorithm, particle swarm algorithm and improved mayfly algorithm are used to estimate the compensation parameters. The experimental results show that the improved mayfly algorithm has obtained faster convergence speed and higher compensation accuracy than others.

摘要

针对ROV配置三轴磁力计近距离测量水下磁性目标磁场特征时存在干扰磁场的问题, 提出了基于改进蜉蝣算法的磁场补偿方法, 以提高水下磁场信息的测量精度。基于三轴磁力计本身的安装误差和ROV的干扰磁场建立了误差补偿模型; 针对原始蜉蝣算法存在易陷入局部最优以及收敛精度差等问题, 引入了Tent混沌序列和Levy飞行变异策略扰动原始蜉蝣算法中陷入局部最优的个体; 利用三轴磁力计测量得到磁场信息, 分别将原始蜉蝣算法、粒子群算法和改进的蜉蝣算法应用于补偿参数的离线寻优估计。试验结果表明改进的蜉蝣算法具有较快的收敛速度以及较高的补偿精度。