Optimization Design Method of Spherical Magnetic Field Generation Coil Based on Differential Evolution Algorithm-Reference-Cited by-同舟云学术

Optimization Design Method of Spherical Magnetic Field Generation Coil Based on Differential Evolution Algorithm

Published:2023-05-20 Issue:3 Volume:27 Page:490-495
ISSN:1883-8014
Container-title:Journal of Advanced Computational Intelligence and Intelligent Informatics
language:en
Short-container-title:JACIII

Author:

Xu Wei¹²³^ORCID,Ge Jian¹²³⁴^ORCID,Yu Hong¹²³^ORCID,Xiao Min¹²³^ORCID

Affiliation:

1. School of Automation, China University of Geosciences, 388 Lumo Road, Wuhan, Hubei 430074, China

2. Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China

3. Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education, Wuhan 430074, China

4. School of Engineering, University of British Columbia, EME4242, 1137 Alumni Avenue, Kelowna, British Columbia V1V 1V7, Canada

Abstract

In a coil magnetometer, the size and uniformity of the bias magnetic field generated by the Helmholtz coil directly determine the accuracy of the solution of the geomagnetic direction. The design of traditional spherical coils relies heavily on the manual experience or mathematical derivation, making it difficult to obtain optimal parameters or requiring larger spherical coils. To address the problem, first, a coaxial symmetrical spherical coil model that improves space utilization was established. Second, an optimal design method for the spherical magnetic field generation coil based on a differential evolution algorithm was proposed. Third, the optimal bias magnetic field was obtained without increasing the volume of the coil. The verification results showed that the magnetic non-uniformity and magnetic gradient of the bias field generated by the optimized coil were reduced by 63.2% and 82.8%, respectively.

Funder

National Natural Science Foundation of China

National Key R&D Program of China

Young Top-notch Talent Cultivation Program of Hubei Province

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

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