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RIS citation export for MOPC02: Identification of Faulty Beam Position Monitor Based Clustering by Fast Search and Find of Density Peaks

TY  - CONF
AU  - Jiang, R.
AU  - Chen, F.Z.
AU  - Chen, Z.C.
AU  - Leng, Y.B.
ED  - Schaa, Volker RW
TI  - Identification of Faulty Beam Position Monitor Based Clustering by Fast Search and Find of Density Peaks
J2  - Proc. of IBIC2018, Shanghai, China, 09-13 September 2018
CY  - Shanghai, China
T2  - International Beam Instrumentation Conference
T3  - 7
LA  - english
AB  - 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. A proper method detecting faulty beam position monitor or monitoring their stability could optimize accel-erator operating conditions. With development in ma-chine learning methods, a series of powerful analysis approaches make it possible for detecting beam position monitor’s stability. Here, this paper proposed a clustering analysis approach to detect the defective BPMs. The method is based on the idea that cluster centres are char-acterized by a higher density than their neighbours and by a relatively large distance from points with higher densi-ties. The results showed that clustering by fast search and find of density peaks could classify beam data into dif-ferent clusters on the basis of their similarity. And that, aberrant data points could be detected by decision graph. So the algorithm is appropriate for BPM detecting and it could be a significant supplement for data analysis in accelerator physics.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 114
EP  - 117
KW  - SRF
KW  - storage-ring
KW  - electron
KW  - electronics
KW  - operation
DA  - 2019/01
PY  - 2019
SN  - 978-3-95450-201-1
DO  - DOI: 10.18429/JACoW-IBIC2018-MOPC02
UR  - http://jacow.org/ibic2018/papers/mopc02.pdf
ER  -