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JACIII Vol.27 No.3 pp. 490-495
doi: 10.20965/jaciii.2023.p0490
(2023)

Research Paper:

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

Wei Xu*1,*2,*3 ORCID Icon, Jian Ge*1,*2,*3,*4,† ORCID Icon, Hong Yu*1,*2,*3 ORCID Icon, and Min Xiao*1,*2,*3 ORCID Icon

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

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

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

*4School of Engineering, University of British Columbia
EME4242, 1137 Alumni Avenue, Kelowna, British Columbia V 1, Canada

Corresponding author

Received:
November 12, 2022
Accepted:
February 8, 2023
Published:
May 20, 2023
Keywords:
bias magnetic field, spherical coil, differential evolution algorithm, non-uniformity, magnetic gradient
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.

Cite this article as:
W. Xu, J. Ge, H. Yu, and M. Xiao, “Optimization Design Method of Spherical Magnetic Field Generation Coil Based on Differential Evolution Algorithm,” J. Adv. Comput. Intell. Intell. Inform., Vol.27 No.3, pp. 490-495, 2023.
Data files:
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