JACoW is a publisher in Geneva, Switzerland that publishes the proceedings of accelerator conferences held around the world by an international collaboration of editors.
@inproceedings{rybnikov:icalepcs2023-thpdp017,
author = {V. Rybnikov and A. Sulc},
title = {{A Data Acquisition Middle Layer Server with Python Support for Linac Operation and Experiments Monitoring and Control}},
% booktitle = {Proc. ICALEPCS'23},
booktitle = {Proc. 19th Int. Conf. Accel. Large Exp. Phys. Control Syst. (ICALEPCS'23)},
eventdate = {2023-10-09/2023-10-13},
pages = {1330--1334},
paper = {THPDP017},
language = {english},
keywords = {cavity, FEL, controls, operation, experiment},
venue = {Cape Town, South Africa},
series = {International Conference on Accelerator and Large Experimental Physics Control Systems},
number = {19},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {02},
year = {2024},
issn = {2226-0358},
isbn = {978-3-95450-238-7},
doi = {10.18429/JACoW-ICALEPCS2023-THPDP017},
url = {https://jacow.org/icalepcs2023/papers/thpdp017.pdf},
abstract = {{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. }},
}