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001     625301
005     20250416150453.0
024 7 _ |a Sulc:2024uag
|2 INSPIRETeX
024 7 _ |a inspire:2788865
|2 inspire
024 7 _ |a arXiv:2405.12391
|2 arXiv
024 7 _ |a 10.3204/PUBDB-2025-01089
|2 datacite_doi
037 _ _ |a PUBDB-2025-01089
041 _ _ |a English
088 _ _ |a arXiv:2405.12391
|2 arXiv
100 1 _ |a Sulc, Antonin
|0 P:(DE-H253)PIP1096696
|b 0
|e Corresponding author
|u desy
245 _ _ |a Automated anomaly detection on European XFEL klystrons
260 _ _ |c 2024
336 7 _ |a Preprint
|b preprint
|m preprint
|0 PUB:(DE-HGF)25
|s 1742303072_4127449
|2 PUB:(DE-HGF)
336 7 _ |a WORKING_PAPER
|2 ORCID
336 7 _ |a Electronic Article
|0 28
|2 EndNote
336 7 _ |a preprint
|2 DRIVER
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a Output Types/Working Paper
|2 DataCite
500 _ _ |a 4 pages, 4 figures, 15, 15TH International Particle Accelerator Conference
520 _ _ |a High-power multi-beam klystrons represent a key component to amplify RF to generate the accelerating field of the superconducting radio frequency (SRF) cavities at European XFEL. Exchanging these high-power components takes time and effort, thus it is necessary to minimize maintenance and downtime and at the same time maximize the device's operation. In an attempt to explore the behavior of klystrons using machine learning, we completed a series of experiments on our klystrons to determine various operational modes and conduct feature extraction and dimensionality reduction to extract the most valuable information about a normal operation. To analyze recorded data we used state-of-the-art data-driven learning techniques and recognized the most promising components that might help us better understand klystron operational states and identify early on possible faults or anomalies.
536 _ _ |a 6G13 - Accelerator of European XFEL (POF4-6G13)
|0 G:(DE-HGF)POF4-6G13
|c POF4-6G13
|f POF IV
|x 0
588 _ _ |a Dataset connected to DataCite, INSPIRE
650 _ 7 |a Accelerator Physics
|2 Other
650 _ 7 |a mc6-beam-instrumentation-controls-feedback-and-operational-aspects - MC6: Beam Instrumentation, Controls, Feedback, and Operational Aspects
|2 Other
650 _ 7 |a MC6.T22 - MC6.T22 Reliability, Operability
|2 Other
650 _ 7 |a klystron
|2 autogen
650 _ 7 |a operation
|2 autogen
650 _ 7 |a acceleration
|2 autogen
650 _ 7 |a timing
|2 autogen
650 _ 7 |a embedded
|2 autogen
693 _ _ |0 EXP:(DE-MLZ)NOSPEC-20140101
|5 EXP:(DE-MLZ)NOSPEC-20140101
|e No specific instrument
|x 0
700 1 _ |a Eichler, Annika
|0 P:(DE-H253)PIP1087213
|b 1
|u desy
700 1 _ |a Wilksen, Tim
|0 P:(DE-H253)PIP1007238
|b 2
|u desy
856 4 _ |y OpenAccess
|u https://bib-pubdb1.desy.de/record/625301/files/2405.12391v1.pdf
856 4 _ |y OpenAccess
|x pdfa
|u https://bib-pubdb1.desy.de/record/625301/files/2405.12391v1.pdf?subformat=pdfa
909 C O |o oai:bib-pubdb1.desy.de:625301
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |a Deutsches Elektronen-Synchrotron
|0 I:(DE-588b)2008985-5
|k DESY
|b 0
|6 P:(DE-H253)PIP1096696
910 1 _ |a Deutsches Elektronen-Synchrotron
|0 I:(DE-588b)2008985-5
|k DESY
|b 1
|6 P:(DE-H253)PIP1087213
910 1 _ |a European XFEL
|0 I:(DE-588)1043621512
|k XFEL.EU
|b 1
|6 P:(DE-H253)PIP1087213
910 1 _ |a Deutsches Elektronen-Synchrotron
|0 I:(DE-588b)2008985-5
|k DESY
|b 2
|6 P:(DE-H253)PIP1007238
913 1 _ |a DE-HGF
|b Forschungsbereich Materie
|l Großgeräte: Materie
|1 G:(DE-HGF)POF4-6G0
|0 G:(DE-HGF)POF4-6G13
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-600
|4 G:(DE-HGF)POF
|v Accelerator of European XFEL
|x 0
914 1 _ |y 2024
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a Published
|0 StatID:(DE-HGF)0580
|2 StatID
920 1 _ |0 I:(DE-H253)MCS_4-20120731
|k MCS 4
|l Beschleunigerkontrollen (FLASH/XFEL)
|x 0
980 _ _ |a preprint
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-H253)MCS_4-20120731
980 1 _ |a FullTexts

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