在多种热发光剂量计类型的自动发光峰标识软件中实现随机梯度下降
Jordan D Noey1, Colin J Stewart, Wenjin Yu
1Department of Nuclear Engineering and Radiological Sciences, University of Michigan, 2355 Bonisteel Boulevard, Ann Arbor, MI 48109-2104.
Health physics
|January 10, 2025
概括
一个新的热发光剂量计 (TLD) 发光曲线分析代码增强了自动峰值检测和曲线拟合. 这种改进的软件显著增加了检测到的峰值,并将平均优点数字降低了46%.
科学领域:
- 物理 物理学 物理
- 材料科学 材料科学 材料科学
- 计算科学 计算科学
背景情况:
- 热发光剂量计 (TLD) 发光曲线的自动分析对于精确的辐射剂量计至关重要.
- 之前的C++代码使用了基于导数的峰值检测和Levenberg-Marquardt匹配.
- 需要进行改进,以提高TLD发光曲线分析的稳定性和准确性.
研究的目的:
- 开发和评估一种改进的C++代码,用于自动化热发光剂量计发光曲线分析.
- 为了增强TLD数据的自动峰值检测和曲线拟合算法.
- 通过使用优点数据,比较新软件版本与前一个软件版本的性能.
主要方法:
- 实现了用于自动检测峰值的静态梯度下降算法,取代了衍生方法.
- 整合了早期停止机制,以优化莱文伯格-马奎特算法用于曲线拟合.
- 在各种热发光剂量计材料上进行了比较性发光曲线分析.
主要成果:
- 更新后的代码显示了自动化峰值检测能力的改进.
- 值得注意的是,平均功绩数量显著下降 (约为46%).
- 与以前的软件版本相比,检测到的峰值的数量增加了.
结论:
- 增强的光曲线分析代码为TLD数据处理提供了卓越的性能.
- 新的算法导致更准确和可靠的剂量测量结果.
- 这一进步有助于在各种应用中提高辐射测量精度.
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