Paper |
Title |
Page |
WEPV007 |
Machine Learning Projects at the 1.5-GeV Synchroton Light Source DELTA |
631 |
|
- D. Schirmer, A. Althaus, S. Hüser, S. Khan, T. Schüngel
DELTA, Dortmund, Germany
|
|
|
In recent years, several machine learning (ML) based projects have been developed to support automated monitoring and operation of the DELTA electron storage ring facility. This includes self-regulating global and local orbit correction of the stored electron beam, betatron tune feedback as well as electron transfer rate (injection) optimization. Furthermore, the implementation for a ML-based chromaticity control is currently prepared. Some of these processes were initially simulated and then successfully transferred to real machine operation. This report provides an overview of the current status of these projects.
|
|
DOI • |
reference for this paper
※ https://doi.org/10.18429/JACoW-ICALEPCS2021-WEPV007
|
|
About • |
Received ※ 10 October 2021 Accepted ※ 21 November 2021
Issue date ※ 02 February 2022 |
|
Cite • |
reference for this paper using
※ BibTeX,
※ LaTeX,
※ Text/Word,
※ RIS,
※ EndNote (xml)
|
|
|