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URLhttps://doi.org/10.18429/JACoW-IPAC2025-THPM016
TitleNeural networks approach for controlling a waveform pattern of the paint bump power supply at J-PARC RCS
Authors
  • M. Sugita, Y. Kuriyama
    Japan Proton Accelerator Research Complex
  • K. Horino, M. Nomura, S. Shinozaki, T. Takayanagi, T. Ueno
    Japan Atomic Energy Agency
AbstractFour horizontal paint bump magnets and two vertical paint bump magnets are used for the painting injection to produce a high intensity beam at J-PARC RCS. These paint bump power supplies are composed of the IGBT chopper units, and so the requirement waveforms can be controlled with high precision less than 1%. By using software that automatically creates input voltage (IV) patterns according to the characteristics of the power supply and direct manual adjustment of IV patterns, the current deviation of the painting pattern (PP) is less than ±0.2%.The adjustment of one PP needs about one hour and several days to adjust a total of 90 patterns with six paint bump magnets. Therefore, a reduction in adjustment time is required. In addition, to mitigate the beam loss caused by beam orbit control to a minimum level, we would like to realize a more precise current deviation. To adjust for these PP, we performed neural networks (NN) approach. By learning the IV patterns and output current patterns as training data, the highly accurate IV patterns were confirmed.The presentation reports on the preliminary training results using NN.
Paperdownload: THPM016.pdf
CiteBibTeX, LaTeX, Text/Word, RIS, EndNote
Conference16th International Particle Accelerator Conference
Series
LocationTaipei, Taiwan
Date01-06 Jun 2025
PublisherJACoW Publishing, Geneva, Switzerland
Editorial Board* Ming-Chyuan Lin - National Synchrotron Radiation Research Center * Yoichi Sato - KEK * Jui-Che Huang - National Synchrotron Radiation Research Center * David Button - Australian Nuclear Science and Technology Organisation * Ping-Shun Chuang - National Synchrotron Radiation Research Center
Online ISBN978-3-95450-248-6
Online ISSN2673-5490
Received28 May 2025
Revised14 October 2025
Accepted14 October 2025
Issued05 November 2025
DOI10.18429/JACoW-IPAC2025-THPM016
Pages2715-2717