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RIS citation export for THPDP017: A Data Acquisition Middle Layer Server with Python Support for Linac Operation and Experiments Monitoring and Control

TY  - CONF
AU  - Rybnikov, V.
AU  - Sulc, A.
ED  - Schaa, Volker RW
ED  - Götz, Andy
ED  - Venter, Johan
ED  - White, Karen
ED  - Robichon, Marie
ED  - Rowland, Vivienne
TI  - A Data Acquisition Middle Layer Server with Python Support for Linac Operation and Experiments Monitoring and Control
J2  - Proc. of ICALEPCS2023, Cape Town, South Africa, 09-13 October 2023
CY  - Cape Town, South Africa
T2  - International Conference on Accelerator and Large Experimental Physics Control Systems
T3  - 19
LA  - english
AB  - This paper presents online anomaly detection on low-level radio frequency (LLRF) cavities running on FLASH/XFEL DAQ system. The code is run by a DAQ Middle Layer (ML) server, which has on-line access to all collected data. The ML server executes a Python script that runs a pre-trained machine learning model on every shot in the FLASH/XFEL machine. We discuss the challenges associated with real-time anomaly detection due to high data rates generated by RF cavities, and introduce a DAQ system pipeline and algorithms used for online detection on arbitrary channels in our control system. The system’s performance is evaluated using real data from operational RF cavities. We also focus on the DAQ monitor server’s features and its implementation. 
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 1330
EP  - 1334
KW  - cavity
KW  - FEL
KW  - controls
KW  - operation
KW  - experiment
DA  - 2024/02
PY  - 2024
SN  - 2226-0358
SN  - 978-3-95450-238-7
DO  - doi:10.18429/JACoW-ICALEPCS2023-THPDP017
UR  - https://jacow.org/icalepcs2023/papers/thpdp017.pdf
ER  -