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Other Keywords |
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| WED04 |
Precise Analysis of Beam Optics at the VEPP-4M by Turn-by-Turn Betatron Phase Advance Measurement |
collider, lattice, betatron, experiment |
79 |
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- I.A. Morozov, P.A. Piminov, I.S. Yakimov
BINP SB RAS, Novosibirsk, Russia
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Turn-by-turn (TbT) beam centroid signals can be used to evaluate various relevant accelerator parameters including betatron frequencies and optical functions. Accurate estimation of parameters and corresponding variances are important to drive accelerator lattice correction. Signals acquired from beam position monitors (BPMs) are limited by beam decoherence and BPM resolution. Therefore, it is important to obtain accurate estimations from available data. Several methods based on harmonic analysis of TbT data are compared and applied to the VEPP-4M experimental signals. The accuracy of betatron frequency, amplitude, and phase measurements are investigated. Optical functions obtained from amplitudes and phases are compared.
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Slides WED04 [3.771 MB]
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| DOI • |
reference for this paper
※ doi:10.18429/JACoW-RuPAC2021-WED04
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| About • |
Received ※ 12 September 2021 — Revised ※ 20 September 2021 — Accepted ※ 23 September 2021 — Issued ※ 20 October 2021 |
| Cite • |
reference for this paper using
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| WEPSC40 |
Detection of Anomalies in BPM Signals at the VEPP-4M |
ISOL, detector, experiment, simulation |
420 |
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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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| Cite • |
reference for this paper using
※ BibTeX,
※ LaTeX,
※ Text/Word,
※ RIS,
※ EndNote (xml)
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