基于改进遗传算法的X波段驻波加速结构优化

针对X波段驻波轴耦合加速管设计,本文提出一种基于改进遗传算法的加速结构多参数自动优化方法。该方法采用MATLAB与电磁仿真软件CST协同,将结构的多个参量进行同时优化,以求得高有效分流阻抗的加速腔结构尺寸。该方法与传统单变量优化方法相比较,可大大节省优化时间,提高了设计效率,同时增加了保持腔体工作频率不变的功能,优化过程中自动调整工作频率至9300MHz,与CST自带遗传优化算法相比更加准确,并缩短了约49.3%的优化时间。对所优化的加速结构进行了加工测试,测试结果验证了优化方案的正确性。

Optimization of X-Band Standing Wave Accelerating Structure Based on Improved Genetic Algorithm

For the design of X-band standing wave axis coupling accelerating tubes,an improved genetic algorithm is proposed to optimize the structure automatically.In this method,several structure parameters are optimized simultaneously by used MATLAB and CST,and the structure parameters of the accelerating cavity with high shunt impedance are obtained.Compared with traditional single-variable optimization method,this method can greatly save optimization time and improve design efficiency.At the same time,it has the function of keeping the working frequency of the cavity constant,and the working frequency will be automatically adjusted to 9300 MHz in the optimization process.The optimization method is more accurate than CST with genetic algorithm,and the optimization time is reduced by 49.3%.The optimized acceleration structure is processed and the test results verify the correctness of the method.