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RIS citation export for THPOPA15: Anomaly Detection Based Quench Detection System for CW Operation of SRF Cavities

TY  - CONF
AU  - Martino, G.
AU  - Aderhold, S.
AU  - Bellandi, A.
AU  - Benwell, A.L.
AU  - Branlard, J.
AU  - Doolittle, L.R.
AU  - Eichler, A.
AU  - Fey, G.
AU  - Gonnella, D.
AU  - Hoobler, S.L.
AU  - Nelson, J.
AU  - Porter, R.D.
AU  - Ratti, A.
AU  - Schlarb, H.
AU  - Zacarias, L.M.
ED  - McIntosh, Peter
ED  - Burt, Graeme
ED  - Apsimon, Robert
ED  - Schaa, Volker R.W.
TI  - Anomaly Detection Based Quench Detection System for CW Operation of SRF Cavities
J2  - Proc. of LINAC2022, Liverpool, UK, 28 August-02 September 2022
CY  - Liverpool, UK
T2  - International Linear Accelerator Conference
T3  - 31
LA  - english
AB  - Superconducting radio frequency (SRF) cavities are used in modern particle accelerators to take advantage of their very high quality factor (Q). A higher Q means that a higher RF field can be sustained, and a higher acceleration can be produced in the cavity for length unity. However, in certain situations, e.g., too high RF field, the SRF cavities can experience quenches that risk creating damage due to the rapid increase in the heat load. This is especially negative in continuous wave (CW) operation due to the impossibility of the system to recover during the off-load period. The design goal of a quench-detection system is to protect the system without being a limiting factor during the operation. In this paper, we compare two different classification approaches for improving a quench detection system. We perform tests using traces recorded from LCLS-II and show that the ARSENAL classifier outperforms a CNN classifier in terms of accuracy.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 775
EP  - 777
KW  - cavity
KW  - experiment
KW  - SRF
KW  - operation
KW  - superconductivity
DA  - 2022/09
PY  - 2022
SN  - 2226-0366
SN  - 978-3-95450-215-8
DO  - doi:10.18429/JACoW-LINAC2022-THPOPA15
UR  - https://jacow.org/linac2022/papers/thpopa15.pdf
ER  -