Speaker
Javier Martínez Samblas
(European Organization for Nuclear Research)
Description
We have developed a new automated system to continuously monitor the health and performance of the LHC Beam Position Monitors (BPMs) at CERN. We preprocess turn-by-turn and bunch-by-bunch data through denoising and normalization before analyzing it using a combination of basic quality tests with rule-based checks and anomaly detection algorithms. All real-time acquisitions are processed on a dedicated python node, with results stored in HDF5 format and aggregated via our offline analysis framework that offers also visualization and reporting functionality. Our system provides robust diagnostics, daily summaries, and dashboards to ensure BPM reliability and maintain high data quality throughout LHC operations.
| Paper status | Resubmitted proceeding files received and assigned to an editor. Accepted. |
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Author
Javier Martínez Samblas
(European Organization for Nuclear Research)
Co-authors
Mr
Andrea Boccardi
(European Organization for Nuclear Research)
Manuel Gonzalez-Berges
(European Organization for Nuclear Research)
Michal Krupa
(European Organization for Nuclear Research)