Abstract: 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.

Key words: synchrotron radiation, beam position monitor (BPM), β oscillation, beam position monitor noise, beam position monitor troubleshooting

摘要： 束流位置监测器（BPMs）对于监测束流的稳定运动至关重要。保持束流的正常运动是上海同步辐射装置的重要任务。有效的诊断分析是完成这一任务的重要途径。本文基于聚类分析开发了一种新方法，利用基本的运行数据，即X和Y方向的β振荡和噪声数据，对束流位置监测器的健康状况进行诊断。分析结果表明，所有束流位置监测器（140个BPMs）可以被分为三组：正常组、性能较差组和故障组。此外，该方法还能标记出异常的束流位置监测器，包括性能较差的。新方法展示了其处理故障束流位置监测器的能力，并能指导日常维护；另一方面，将成为加速器物理数据分析的有益补充。

关键词: 同步辐射，束流位置监测器（BPM），β振荡，BPM噪声，BPM故障排查