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Diagnostic Method for Beam Position Monitor Based on Clustering by Fast Search and Find of Density Peaks

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摘要 Beam position monitors(BPMs)are important to monitor the beam moving steadily.Keeping the beam's normal motion is an important mission for Shanghai Synchrotron Radiation Facility.Effective diagnostic analysis is an important way to accomplish this task.This paper develops a new method based on clustering analysis to diagnose the healthy of BPMs with basic running data,i.e.,the β oscillation of X and Y directions and noise data.The analysis results showed that all beam position monitors(140 BPMs)can be classified into three groups:normal group,worse performance group,and fault group,respectively.In addition,the abnormal BPMs(including worse performance)could be marked.The new method showed its ability to handle faulty BPMs and it could instruct daily maintenance.On the other hand,it will be a useful supplement for data analysis in accelerator physics.
作者 姜瑞涛 杨星 邓又铭 冷用斌 JIANG Ruitao;YANG Xing;DENG Youming;LENG Yongbin(Shanghai Synchrotron Radiation Facility,Shanghai Advanced Research Institute,Chinese Academy of Sciences,Shanghai 201204,China;Shanghai Institute of Applied Physics,Chinese Academy of Sciences,Shanghai 201800,China)
出处 《Journal of Shanghai Jiaotong university(Science)》 EI 2024年第3期457-462,共6页 上海交通大学学报(英文版)
基金 Ten Thousand Talent Program and Chinese Academy of Sciences Key Technology Talent Program (No.Y91G201B01)。
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