Optics and Precision Engineering, Volume. 30, Issue 14, 1749(2022)
CSA-NSGAII algorithm for magnetically shielded room shield lamination optimization
To improve the shielding performance of a multilayer magnetically shielded structure and to further reduce the construction cost of a magnetically shielded room, this study proposes to treat the magnetically shielded structure as a multi-objective function optimization problem, and to optimize the parameters of the shielded lamination structure using the non-dominated sorting genetic algorithm-II (NSGAII) under the constraints of feasible construction cost and quality construction composition. In this study, the NSGAII algorithm is improved using a segmental crossover strategy with an adaptive variation operator called CSA-NSGAII to solve the problems of the traditional NSGAII algorithm of uneven population convergence distribution, poor global search ability, and easily falling into a local optimum. Compared with the original NSGAII algorithm, NSGAII-SDR, g-NSGAII, and MOEA/D algorithms, the CSA-NSGAII is beneficial in GD, IGD, and spacing, indicating that the proposed CSA-NSGAII algorithm achieves improved convergence performance and a more uniform population distribution. By applying the algorithm proposed in this paper to the multi-objective optimization design problem of the magnetic shielding structure, the experimental results show that the optimized stacked structure can, on average, save approximately 14% of the construction costs while achieving the same shielding performance, and can achieve approximately 70 dB of shielding performance in a Helmholtz coil with an interference amplitude of 32 000 nT and frequency of 1 Hz.
Get Citation
Copy Citation Text
Songnan YANG, Xiaohui ZHANG, Yuanyuan LIU, Jinsheng ZHANG, Xiaoli XI. CSA-NSGAII algorithm for magnetically shielded room shield lamination optimization[J]. Optics and Precision Engineering, 2022, 30(14): 1749
Category: Information Sciences
Received: Apr. 20, 2022
Accepted: --
Published Online: Sep. 6, 2022
The Author Email: ZHANG Xiaohui (xhzhang@xaut.edu.cn)