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| WEPSC40 |
Detection of Anomalies in BPM Signals at the VEPP-4M |
detector, experiment, optics, simulation |
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- I.A. Morozov, P.A. Piminov
BINP SB RAS, Novosibirsk, Russia
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Beam position monitors (BPMs) are widely used for beam diagnostics in particle accelerators. Turn-by-turn (TbT) beam centroid data provide a means to estimate performance-critical accelerator parameters, like betatron frequency and optical functions. Parameter estimation accuracy is heavily related to TbT data quality. BPM faults might lead to erroneous estimation of accelerator parameters and should be accounted for achieving accurate and reliable results. Several anomaly detection methods for TbT data cleaning are considered. Derived features of BPM signals along with their robust dispersion estimation are used to flag faulty BPM signals. Estimated contamination factor is used with unsupervised learning methods (Local Outlier Factor and Isolation Forest). Application of anomaly detection methods for the VEPP-4M experimental TbT data is reported.
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Poster WEPSC40 [2.681 MB]
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| DOI • |
reference for this paper
※ doi:10.18429/JACoW-RuPAC2021-WEPSC40
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| About • |
Received ※ 05 September 2021 — Accepted ※ 20 September 2021 — Issued ※ 21 September 2021 |
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