通过新的介电光谱标记器和机器学习算法对核电缆中的玛辐射衰老进行非破坏性评估
Ahmad Abualasal1, Zoltán Ádám Tamus1
1Department of Electric Power Engineering, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, H-1111 Budapest, Hungary.
Polymers
|February 27, 2026
概括
本研究引入了一种非破坏性方法,使用介电光谱来评估核电站电缆中的辐射损伤. 它可以根据介电性质准确地诊断降解的乙烯基 (EPR) 和硫聚乙烯 (CSPE) 隔热.
科学领域:
- 核工程 核工程是指核工程.
- 材料科学 材料科学 材料科学
- 电气工程 电气工程
背景情况:
- 核设施中的仪表和控制 (I&C) 电缆随着时间的推移因持续马 (γ) 辐射暴露而降解.
- 传统的电缆老化的机械评估具有破坏性,限制了它们在运行中的核电站中的应用.
研究的目的:
- 开发和验证一种非破坏性诊断框架,用于评估低压I&C电缆的辐射诱导退化.
- 为了确定辐射剂量和电缆绝缘材料可测量的介电性质之间的相关性.
主要方法:
- 利用高频介电谱学分析辐射电缆样本的宽带介电反应.
- 用乙烯烯 (EPR) 绝缘和硫化聚乙烯 (CSPE) 覆盖的电缆样本接受控制的马 (γ) 辐射,最高可达1200kGy.
- 采用机器学习算法来分析介电数据,包括电容和损失触角光谱,以导出诊断参数.
主要成果:
- 对EPR绝缘和CSPE外套的辐射剂量和介电指标之间确定了强烈的,特定于材料的关系.
- 证明中央电容 (CC) 和 (C × F × LF) 分别是黑色和白色EPR的敏感指标.
- 观察到中央频率 (CF) 的单调下降,CSPE外套的辐射暴露增加.
结论:
- 开发的介电光谱框架为核电站中辐射受损电缆的诊断提供了准确而非破坏性的方法.
- 识别的介电参数提供了由于玛辐射导致电缆老化的直接和透明的解释.
- 这种方法可以通过可靠的电缆状况监测来提高核设施的安全性和运行效率.
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