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RIS citation export for WEPV025: Initial Studies of Cavity Fault Prediction at Jefferson Laboratory

AU  - Vidyaratne, L.S.
AU  - Carpenter, A.
AU  - Iftekharuddin, K.M.
AU  - Rahman, M.
AU  - Suleiman, R.
AU  - Tennant, C.
AU  - Turner, D.L.
ED  - Furukawa, Kazuro
ED  - Yan, Yingbing
ED  - Leng, Yongbin
ED  - Chen, Zhichu
ED  - Schaa, Volker R.W.
TI  - Initial Studies of Cavity Fault Prediction at Jefferson Laboratory
J2  - Proc. of ICALEPCS2021, Shanghai, China, 14-22 October 2021
CY  - Shanghai, China
T2  - International Conference on Accelerator and Large Experimental Physics Control Systems
T3  - 18
LA  - english
AB  - The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory is a CW recirculating linac that utilizes over 400 superconducting radio-frequency (SRF) cavities to accelerate electrons up to 12 GeV through 5-passes. Recent work has shown that, given RF signals from a cavity during a fault as input, machine learning approaches can accurately classify the fault type. In this paper we report on initial results of predicting a fault onset using only data prior to the failure event. A data set was constructed using time-series data immediately before a fault (’unstable’) and 1.5 seconds prior to a fault (’stable’) gathered from over 5,000 saved fault events. The data was used to train a binary classifier. The results gave key insights into the behavior of several fault types and provided motivation to investigate whether data prior to a failure event could also predict the type of fault. We discuss our method using a sliding window approach and report on initial results. Recent modifications to the low-level RF control system will provide access to streaming signals and we outline a path forward for leveraging deep learning on streaming data
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 700
EP  - 704
KW  - cavity
KW  - cryomodule
KW  - electron
KW  - data-acquisition
DA  - 2022/03
PY  - 2022
SN  - 2226-0358
SN  - 978-3-95450-221-9
DO  - doi:10.18429/JACoW-ICALEPCS2021-WEPV025
UR  - https://jacow.org/icalepcs2021/papers/wepv025.pdf
ER  -