在可见图像中检测和跟踪由磁化同轴等离子体枪产生的高速等离子体
Zhaoxuan Li1,2, Yang Ye2, Defeng Kong2
1School of Materials Science and Engineering, Anhui University of Science and Technology, Huainan 232001, People's Republic of China.
The Review of scientific instruments
|December 4, 2024
概括
一个新的算法使用UNet和SORT方法准确地检测和跟踪tokamak聚变能量至关重要的等离子体. 这支持EAST托卡马克的先进诊断.
科学领域:
- 等离子体物理学的物理学
- 融合能源研究 融合能源研究
- 机器学习应用 机器学习应用
背景情况:
- 紧型Torus (CT) 注射装置,也称为磁化同轴等离子体枪,产生高密度,高速度等离子体.
- 这些等离子体具有显著的能量密度,这使得它们在未来的核聚变反应堆中对托卡马克核燃料供应非常有希望.
- 东部托卡马克配备了一个新开发的CT注射系统 (东部-CTI),需要先进的诊断能力.
研究的目的:
- 开发和验证一种新的算法,用于检测和跟踪来自EAST-CTI系统可见图像中的等离子体.
- 评估算法在识别和跟踪等离子体流中的多个等离子体的准确性和稳定性.
- 为核聚变能源应用中CTs的演变特征提供关键的见解.
主要方法:
- 一个利用UNet神经网络进行等离子体检测的细分模块.
- 一个基于修改的简单在线和实时跟踪 (SORT) 算法用于等离子体识别的跟踪模块.
- 将开发的算法应用于来自EAST-CTI系统的可见成像数据.
主要成果:
- 在测试数据集中,UNet网络获得了0.813的Dice系数,在等离子体检测中显示出高精度.
- 修改后的SORT算法成功追踪了等离子体,没有假阳性或身份错误.
- 该算法有效地识别了EAST-CTI系统弹出的血流中的多个等离子体.
结论:
- 开发的UNet-SORT算法准确地检测和跟踪等离子体,满足EAST-CTI系统的诊断要求.
- 这一进步使得对CT进化特征的关键见解成为可能,这对于核聚变反应堆的发展至关重要.
- 该算法促进了从成像中获得的广泛数据分析,为未来对托卡马克燃料的研究铺平了道路.
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