Time-series deep learning anomaly detection for particle accelerators
D Marcato, D Bortolato, V Martinelli, G Savarese… - IFAC-PapersOnLine, 2023 - Elsevier
High energy particle accelerators rely on superconducting radio frequency cavities to
transfer energy and accelerate the beam. Such particle accelerators are complex and
expensive systems prone to failures which lead to downtime of the whole experimental
facility: it is thus of primary importance to anticipate and prevent these faults to improve the
uptime and cost-effectiveness of particle accelerators. Data-driven methods are especially fit
for this task as they can leverage all the data recorded and archived by a typical control …
transfer energy and accelerate the beam. Such particle accelerators are complex and
expensive systems prone to failures which lead to downtime of the whole experimental
facility: it is thus of primary importance to anticipate and prevent these faults to improve the
uptime and cost-effectiveness of particle accelerators. Data-driven methods are especially fit
for this task as they can leverage all the data recorded and archived by a typical control …
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