通过将先前的知识插入到基于最大树的方法来进行异常分类,以对 WEST 托卡马克的分离器热点进行表征
Valentin Gorse1, Raphaël Mitteau1, Julien Marot2
1CEA, IRFM, F-13108 Saint-Paul-Lez-Durance, France.
The Review of scientific instruments
|December 8, 2023
概括
使用最大树表示的新方法准确地对WEST托卡马克转移器的热点进行分类,提高了融合能源研究的操作安全性. 这种技术避免了标记数据,为传统机器学习模型提供了更快的替代方案.
科学领域:
- 核聚变工程 核聚变工程
- 等离子体物理学的物理学
- 材料科学 材料科学 材料科学
背景情况:
- 西方托卡马克转移器管理高热流,对于等离子控制和排气至关重要.
- 超过热流极限可能会损坏面向等离子体的构件.
- 确保转向器运行安全对于未来的核聚变反应堆,如ITER,至关重要.
研究的目的:
- 开发一种可靠的方法来检测和分类WEST托卡马克分流器表面的热点.
- 通过精确监测转器热状况,提高运行安全.
- 提供适用于ITER的转向器监控解决方案.
主要方法:
- 利用红外 (IR) 温度计进行实时地表温度监测.
- 开发了一种基于最大树表示和图像属性的新型分类方法.
- 应用该方法来分析WEST托卡马克转移器罢工线的IR图像.
主要成果:
- 马克斯树分类器准确地识别了88%的异常热点.
- 该方法证明了高效的计算,适合在托卡马克脉冲之间执行.
- 在不需要标记训练数据的情况下实现分类,与SVM或CNN方法不同.
结论:
- 基于最大树的方法为分离器热点分类提供了可靠和高效的解决方案.
- 这种方法增强了托卡马克主动冷却的转向器的操作安全性.
- 该技术作为ITER转向系统的监控解决方案具有前景.
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