...
首页> 外文期刊>Journal of the Chinese Institute of Engineers >A pitch distribution in slow-wave structure of STWT using Cauchy mutated cat swarm optimization with gravitational search operator
【24h】

A pitch distribution in slow-wave structure of STWT using Cauchy mutated cat swarm optimization with gravitational search operator

机译:使用Cauchy突变的CAT群优化与引力搜索操作员的STWT慢波结构的俯仰分布

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Space traveling-wave tube (STWT) is a special power amplifier used in the space technology field to perform high-power conversion of signals; the pitch distribution is core parameter in slow-wave structure to ensure energy exchange between the electron beam and electromagnetic wave. A novel Cauchy mutated cat swarm optimization with gravitational search operator (GS-CMCSO) is proposed and applied to slow-wave structure design of STWT, electron beam efficiency is used as the objective function, and 1-D CHRISTINE code is introduced to obtain the output value of STWT, the pitch distribution to obtain best beam efficiency can be calculated. Experiments are carried out based on GS-CMCSO; quantum particle swarm optimization (QPSO) and Cauchy mutated cat swarm optimization (CMCSO) algorithms are introduced for optimization performance comparison. The experimental results demonstrate that the best beam efficiency (42.6%) generated by GS-CMCSO is larger than those of CMCSO (40.5%) and QPSO (34.9%); when the STWT is saturated, the output power and gain optimized by GS-CMCSO are excellent. Thus, the proposed method is very suitable for pitch distribution optimization in the slow-wave structure of STWT and performs better than those on QPSO and CMCSO.
机译:空间行波管(STWT)是空间技术领域用于信号高功率转换的专用功率放大器;螺距分布是慢波结构中保证电子束与电磁波能量交换的核心参数。提出了一种新的带引力搜索算子的Cauchy变异猫群优化算法(GS-CMCSO),并将其应用于STWT的慢波结构设计中,以电子束效率为目标函数,引入一维CHRISTINE码获得STWT的输出值,计算出获得最佳束效率的节距分布。基于GS-CMCSO进行了实验;引入量子粒子群优化算法(QPSO)和柯西变异猫群优化算法(CMCSO)进行优化性能比较。实验结果表明,GS-CMCSO产生的最佳光束效率(42.6%)大于CMCSO(40.5%)和QPSO(34.9%);当STWT饱和时,GS-CMCSO优化的输出功率和增益都很好。因此,该方法非常适用于STWT慢波结构中的基音分布优化,其性能优于QPSO和CMCSO。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号