基于遗传算法的电离室结构多目标优化方法

Multi-Objective Optimization of Ionization Chamber Structure Based on Genetic Algorithm

  • 摘要: 电离室是大型客体辐射成像系统重要的组成部分,目前的平行板电离室响应时间过长,难以满足快速检测的需求。栅网型探测器可以大幅缩减探测器的响应时间,但是该型探测器的结构参数众多,且两个主要参数“响应时间”和“输出电流”存在互斥现象,采用枚举法或者经验法进行结构优化设计,效率较低。因此,本研究提出一种基于快速非支配排序遗传算法(NSGAⅡ)的栅网型电离室结构多目标优化方法,在约束条件下对输出电流和响应时间进行优化设计。结果表明,本方法可以快速设计出满足实际需求的电离室,可为结构优化设计提供新思路。

     

    Abstract: Ionization chambers play a crucial role in large-scale radiation imaging systems. However, the response time of conventional parallel-plate ionization chambers is too long to meet the requirements for rapid detection. To address this issue, a grid detector was previously proposed, significantly reducing detector response time. However, optimizing the structure of this type of detector is challenging due to its numerous parameters. In particular, the key parameters—response time and output current—are inherently conflicting, making it inefficient to rely on enumeration or empirical methods for structural optimization. To overcome this limitation, this paper introduces a multi-objective optimization approach based on the NSGA-II algorithm to optimize the response time and output current of grid ionization chambers under given constraints. The results demonstrate that the proposed method efficiently provides a design solution that meets practical requirements, offering a novel approach to the structural optimization of ionization chambers.

     

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