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TY - CONF AU - Jiang, R. AU - Leng, Y.B. ED - Boland, Mark ED - Tanaka, Hitoshi ED - Button, David ED - Dowd, Rohan ED - Schaa, Volker RW ED - Tan, Eugene TI - Application of Clustering by Fast Search and Find of Density Peaks to Beam Diagnostics at SSRF J2 - Proc. of IPAC2019, Melbourne, Australia, 19-24 May 2019 CY - Melbourne, Australia T2 - International Particle Accelerator Conference T3 - 10 LA - english AB - With the increased technological complexity of accelera-tors, meeting the demand of beam diagnostics and opera-tion need more powerful and faster methods. And detect-ing the accuracy and stability of beam position moni-tors(BPMs) are important for all kinds of measurement systems and feedback systems in particle accelerator field. As an effective tool for data analysis and automa-tion, the machine learning methods had been used in accelerator physics field, recently. Among machine learn-ing methods, the clustering by fast search and find of density peaks as a typical unsupervised learning algo-rithms could be performed directly without training in arbitrary accelerator systems and could discover un-known patterns in the data. This paper used clustering by fast search and find of density peaks to detect faulty beam position monitor or monitoring beam orbit stability by analysis five typical parameters, that is beta oscilla-tion of X and Y direction(BetaX and BetaY), transverse oscillation of X and Y direction(AmpX and AmpY) and energy oscillation(AmpE). The results showed that cluster-ing by fast search and find of density peaks could classi-fy beam data into different clusters on the basis of their similarity. And that, aberrant run data points could be detected by decision graph. Morever, analysis results demonstrate the characteristic parameters AmpE, AmpX and BetaX amplitude have the same effect to distinguish the faulty BPMs and the AmpY and the BetaY amplitude are also. PB - JACoW Publishing CP - Geneva, Switzerland SP - 2581 EP - 2583 KW - SRF KW - GUI KW - storage-ring KW - diagnostics KW - electron DA - 2019/06 PY - 2019 SN - 978-3-95450-208-0 DO - DOI: 10.18429/JACoW-IPAC2019-WEPGW045 UR - http://jacow.org/ipac2019/papers/wepgw045.pdf ER -