9-cell超导腔快速预调谐方法研究  被引量:2

Research on fast pre-tuning method of 9-cell superconducting cavities

在线阅读下载全文

作  者:朱航 翟纪元[1,2] 戴建枰 Zhu Hang;Zhai Jiyuan;Dai Jianping(Accelerator Research Center,Institute of High Energy Physics,Chinese Academy of Sciences,Beijing 100049,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区:[1]中国科学院高能物理研究所加速器中心,北京100049 [2]中国科学院大学,北京100049

出  处:《强激光与粒子束》2022年第10期139-143,共5页High Power Laser and Particle Beams

摘  要:对频率和场平坦度的预调谐是9-cell超导腔耗时最多的后处理工序之一,很快将成为国内相关大科学工程9-cell腔批量生产的瓶颈。首先介绍了9-cell超导腔两种常用的预调谐方法,即DESY方法和Cornell方法的原理,建模分析和比较了两种方法的计算精度和误差来源,给出Cornell方法调谐量计算的修正。然后结合9-cell超导腔预调谐实验研究,给出了快速预调谐方法:DESY的重建算法在低场平时精度较高且收敛迅速,可作为粗调;Cornell微扰算法在高场平时精度较高且测量迅速,可作为微调。结合两种调谐方式,将预调谐分为粗调和微调两步,可有效提升9-cell超导腔预调谐的速度。The pre-tuning of frequency and field flatness is one of the most time-consuming post-processing procedures for 9-cell superconducting cavities,and will soon become the bottleneck of mass production of 9-cell cavities in domestic related major scientific projects.In this paper we firstly introduce two commonly used pre-tuning methods for 9-cell superconducting cavities,namely DESY method and Cornell method.Then we analyze and compare their calculation accuracy and error sources by modeling,and make a correction on the Cornell method’s tuning amount calculation.Verifing the pre-tuning of several cavities by the experimental research,we give a fast pretuning method in which DESY reconstruction algorithm is used for coarse-tuning as it has high precision and rapid tuning speed in low field flatness and Cornell perturbation algorithm is used for fine-tuning as it has high precision in high field flatness with faster measurement.Combining these two tuning algorithms,the pre-tuning is divided into two steps:coarse tuning and fine tuning,which can effectively improve the pre-tuning speed of the 9-cell superconducting cavity.

关 键 词:9-cell超导腔 预调谐 场平坦度 拉珠测量 

分 类 号:TL503.2[核科学技术—核技术及应用]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象