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.
JIANG Ruitao(姜瑞涛), YANG Xing(杨星), DENG Youming(邓又铭)，LENG Yongbin(冷用斌)
. Diagnostic Method for Beam Position Monitor Based on Clustering by Fast Search and Find of Density Peaks[J]. Journal of Shanghai Jiaotong University(Science), 2024
, 29(3)
: 457
-462
.
DOI: 10.1007/s12204-022-2546-y
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