| Title |
Progress on Machine Learning for the SNS High Voltage Converter Modulators |
| Authors |
- M.I. Radaideh, S.M. Cousineau, D. Lu
ORNL, Oak Ridge, Tennessee, USA
- T.J. Britton, K. Rajput, M. Schram, L.S. Vidyaratne
JLab, Newport News, Virginia, USA
- G.C. Pappas, J.D. Walden
ORNL RAD, Oak Ridge, Tennessee, USA
|
| Abstract |
The High-Voltage Converter Modulators (HVCM) used to power the klystrons in the Spallation Neutron Source (SNS) linac were selected as one area to explore machine learning due to reliability issues in the past and the availability of large sets of archived waveforms. Progress in the past two years has resulted in generating a significant amount of simulated and measured data for training neural network models such as recurrent neural networks, convolutional neural networks, and variational autoencoders. Applications in anomaly detection, fault classification, and prognostics of capacitor degradation were pursued in collaboration with the Jefferson Laboratory, and early promising results were achieved. This paper will discuss the progress to date and present results from these efforts.
|
| Paper |
download WEPA38.PDF [2.032 MB / 4 pages] |
| Poster |
download WEPA38_POSTER.PDF [1.385 MB] |
| Cite |
download ※ BibTeX
※ LaTeX
※ Text/Word
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※ EndNote |
| Conference |
NAPAC2022 |
| Series |
International Particle Accelerator Conference (5th) |
| Location |
Albuquerque, NM, USA |
| Date |
07-12 August 2022 |
| Publisher |
JACoW Publishing, Geneva, Switzerland |
| Editorial Board |
Sandra Biedron (Element Aero, Chicago, IL, USA); Evgenya Simakov (LANL, Los Alamos, NM, USA); Stephen Milton (Element Aero, Chicago, IL, USA); Petr M. Anisimov (LANL, Los Alamos, NM, USA); Volker R.W. Schaa (GSI, Darmstadt, Germany) |
| Online ISBN |
978-3-95450-232-5 |
| Online ISSN |
2673-7000 |
| Received |
25 July 2022 |
| Revised |
08 August 2022 |
| Accepted |
11 August 2022 |
| Issue Date |
03 October 2022 |
| DOI |
doi:10.18429/JACoW-NAPAC2022-WEPA38 |
| Pages |
715-718 |
| Copyright |
 Published by JACoW Publishing under the terms of the Creative Commons Attribution 4.0 International license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI. |
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