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Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification at Jefferson Laboratory

This work investigates the efficacy of deep learning (DL) for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a large, high-power continuous wave recirculating linac that utilizes 418 SRF cav...

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Detalles Bibliográficos
Autores principales:	Vidyaratne, Lasitha, Carpenter, Adam, Powers, Tom, Tennant, Chris, Iftekharuddin, Khan M., Rahman, Md Monibor, Shabalina, Anna S.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2022
Materias:	Artificial Intelligence
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8762208/ https://www.ncbi.nlm.nih.gov/pubmed/35047766 http://dx.doi.org/10.3389/frai.2021.718950

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