摘要
小角散射实验站用户获取的实验数据质量与实验站的光路优化状态(较低的散射背景、准确的样品前后光强计数等)密切相关。目前小角散射实验站光路优化是手动优化方式,不利于用户机时的有效利用。在实验物理与工业控制系统(Experimental Physics and Industrial Control System,EPICS)和控制系统工具箱(Control System Studio,CSS)平台下,使用Python语言设计并开发了光路优化自动校准程序,通过狭缝刀口扫描确定直通光中心位置,根据遗传算法的单目标和多目标优化方法自动优化,得到较低的空气背底散射图像,最终完成调光。测试结果表明:自动校准程序可以在30 min内完成实验站单色光狭缝和束流阻挡器位置调试,简化了实验站的光路优化工作,提高了小角散射实验站的自动化程度。
[Background]The quality of the experimental data is closely related to the optimal optical conditions of the end-station in the small-angle X-ray scattering(SAXS)beamline(lower scattering background,accurate beam intensity before and after the sample,etc.).At present,the optical conditions of the end-station are manually optimized in SAXS beamline(BL16B1)of shanghai synchrotron radiation facility(SSRF),which can not utilize the user's time effectively.[Purpose]This study aims to design and implement an automatic calibration procedure with Python on the platform of EPICS(experimental physics and industrial control system)and CSS(control system studio).[Methods]Firstly,the direct beam was searched and targeted using slit blades scanning,and then beam center was automatically optimized according to the single-objective and multi-objective optimization methods of genetic algorithm,the calibration is not completed until an optimal scattering background image is obtained.[Results]The results show that the automatic beamline calibration system can complete the motors optimization of slits and beamstop in 30 min,much faster than manual operation.[Conclusions]Proposed automatic calibration system simplifies the optical path optimization of experimental station and improves the automation of the SAXS beamline station at SSRF.
作者
洪春霞
周平
滑文强
杨春明
边风刚
HONG Chunxia;ZHOU Ping;HUAWenqiang;YANG Chunming;BIAN Fenggang(Shanghai Synchrotron Radiation Facility,Shanghai Advanced Research Institute,Chinese Academy of Sciences,Shanghai 201210,China;Shanghai Institute of Applied Physics,Chinese Academy of Sciences,Shanghai 201800,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《核技术》
CAS
CSCD
北大核心
2021年第1期18-24,共7页
Nuclear Techniques
基金
国家重点研发计划(No.2018YFB0704200)资助。