|
Hokkaido University Collection of Scholarly and Academic Papers >
Graduate School of Information Science and Technology / Faculty of Information Science and Technology >
Peer-reviewed Journal Articles, etc >
Quench Prediction for REBCO Pancake Coils Using LSTM
| Title: | Quench Prediction for REBCO Pancake Coils Using LSTM |
| Authors: | Nakai, Yusuke Browse this author | | Noguchi, So Browse this author →KAKEN DB |
| Keywords: | LSTM | | neural network | | quench prediction | | REBCO pancake coils |
| Issue Date: | Aug-2024 |
| Publisher: | IEEE (Institute of Electrical and Electronics Engineers) |
| Journal Title: | IEEE transactions on applied superconductivity |
| Volume: | 34 |
| Issue: | 5 |
| Start Page: | 4703005 |
| Publisher DOI: | 10.1109/TASC.2024.3353719 |
| Abstract: | In this article, we propose a neural network-based quench prediction method. High-temperature superconductors (HTS) has a slower propagation velocity in the local normal-zone than low-temperature superconductors (LTS), and the hotspots are more likely to occur. The cases of coil burnout due to this have been reported, and such quenches are difficult to detect. Several methods have been proposed to detect and protect against quenches, but the coil temperature is already rising when a quench is detected. This means that coil operation must be stopped before the actual quench signal by predicting the occurrence of a quench. In this study, we show the results of quench prediction for unknown data by training data obtained from numerical simulations using a neural network called LSTM. |
| Rights: | © 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Type: | article (author version) |
| URI: | http://hdl.handle.net/2115/92377 |
| Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
|
Submitter: 野口 聡
|
