谷歌浏览器插件
订阅小程序
在清言上使用

Optimal Design for Electric Heating Coil in Atomic Sensors

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT(2024)

引用 0|浏览7
暂无评分
摘要
This article proposes a novel approach to optimize the heating coil of atomic sensors, which can reduce the impact of the heating process on performance. The atomic sensors utilize vapor cells to measure physical quantities by monitoring the precession state of alkali metal atoms, which are influenced by the magnetic field. Achieving a sufficient signal strength requires a high temperature to achieve the desired alkali metal atom density. However, the commonly used electric heating method introduces magnetic interference from the heating current. Therefore, this article proposes an optimal design scheme in 3-D space to mitigate the magnetic field generated by the heating coil in the atomic sensors. By designing vertical and planar structures, the influence of the magnetic field generated during the heating process on alkali metal atoms can be significantly decreased. First, the number of layers in the vertical structure is designed, and a three-layer optimal solution is proposed. Second, the planar structure optimization is designed by using the sparrow search algorithm (SSA) to generate a minimum spatial magnetic field by the heating coil with the same length. The simulation results show that the proposed design coil reduces the magnetic field from 803.44 to 160.72 pT/mA at a distance of 2 mm from the coil, a significant improvement over the 2(N) configuration. Experimental results confirm that the magnetic field generated by the three-layer vertical structure is smaller than that of other multilayer structures, and the magnetic field generated by the optimized coil is smaller than 2(N) coil.
更多
查看译文
关键词
Coils,Heating systems,Magnetic multilayers,Sensors,Magnetometers,Magnetic resonance,Resistance heating,Atomic sensor,electric heating systems,heating coil,magnetic field suppression,sparrow search algorithm (SSA)
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要