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

Internet

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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