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arXiv 2404.06950physics.ins-detnucl-ex
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用于能量-道址校准的康普顿边缘卷积模型与算法

Compton Edge Convolutional Model and Algorithm for Energy-channel Calibration

Yanbiao Zhang, Fanjie Zeng, Dehua Kong, Lian Lei, Zhonghai Wang

AI总结:

针对塑料闪烁体等探测器全能峰不显著、校准需手动调整的难题,提出康普顿边缘卷积模型,经多种探测器和¹³⁷Cs源测试,校准误差在1%以内。

摘要:

闪烁探测器是辐射测量的核心工具,但对其进行精准校准颇具难度,尤其是在全能峰不显著的情况下——这一问题在塑料闪烁体等探测器中十分常见。目前这类探测器的校准方法往往需要手动调整。为解决该问题,我们提出了一种名为卷积模型的新方法,该模型可精准校准多种探测器中康普顿边缘的能量-道址关系。我们使用塑料闪烁体BC408、NaI晶体和LaBr₃晶体开展测试,借助¹³⁷Cs放射源,先用全能峰对NaI和LaBr₃探测器进行校准,再采用卷积模型拟合康普顿边缘。结果显示,与全能峰校准相比,该方法的误差在1%以内。

英文摘要:

Scintillation detectors are essential tools for radiation measurement, but calibrating them accurately can be challenging, especially when full-energy peaks are not prominent. This is common in detectors like plastic scintillators. Current methods for calibrating these detectors often require manual adjustments. To address this, we propose a new method called the convolution model. This model accurately calibrates the energy-channel relationship of the Compton edge in various detectors. We tested it with plastic scintillator BC408, NaI crystal, and LaBr$_3$ crystal. Using ${}^{137}$Cs radioactive sources, we calibrated NaI and LaBr$_3$ detectors using full-energy peaks, then applied the convolution model to fit the Compton edge. Our results show errors within 1\% when compared to full-energy peak calibration.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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