摘要
高质量的电子束流寿命数据可以直接反映装置的健康状态,为了获得高质量的束流寿命数据,提出一种束流寿命数据清洗方法,并开展了影响束流寿命的关键因素研究。基于合肥光源历史数据库对2022年以来累积的束流寿命原始数据进行分析,采用Python开发了自动化数据清洗程序,用于获取和处理合肥光源的原始束流寿命数据,以获得长时间跨度的束流寿命变化趋势。通过使用Pearson相关系数对束流寿命异常原因进行分析,发现合肥光源束流寿命受储存环真空压强和高频腔压的影响较大。该束流寿命清洗程序处理快捷,获取的高质量束流寿命数据可以为合肥光源的健康状态检测诊断和预警提供重要依据。
High-quality electron beam lifetime data directly reflects the health status of the facility.In order to obtain high-quality beam lifetime data,this paper proposes a beam lifetime data cleaning method and conducts research on key factors affecting beam lifetime.Based on the raw beam lifetime data stored in the Hefei Light Source historical database since 2022,an automated data cleaning program was developed using Python to acquire and process the original beam lifetime data of Hefei Light Source,in order to obtain the long-term trend of beam lifetime variation.By analyzing the reasons for beam lifetime anomalies using the Pearson correlation coefficient,it was found that the beam lifetime of Hefei Light Source is significantly influenced by the storage ring vacuum pressure and the high-frequency cavity voltage.The beam lifetime cleaning program is efficient,and the obtained high-quality beam lifetime data can provide important information for health status monitoring,diagnostics,and early warning of Hefei Light Source.
作者
杨锐
余海山
孙晓康
汪冠良
宣科
刘功发
YANG Rui;YU Haishan;SUN Xiaokang;WANG Guanliang;XUAN Ke;LIU Gongfa(National Synchrotron Radiation Laboratory,University of Science and Technology of China,Hefei 230029,China)
出处
《核电子学与探测技术》
CAS
北大核心
2024年第1期131-138,共8页
Nuclear Electronics & Detection Technology
基金
国家自然基金委青年科学基金项目(No.12205295)。
