Intelligent Computing Laboratory, Korea Atomic Energy Research Institute, Daejeon 34507, Korea.
Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea.
Sensors (Basel). 2020 May 20;20(10):2895. doi: 10.3390/s20102895.
Plastic scintillation detectors are widely utilized in radiation measurement because of their unique characteristics. However, they are generally used for counting applications because of the energy broadening effect and the absence of a photo peak in their spectra. To overcome their weaknesses, many studies on pseudo spectroscopy have been reported, but most of them have not been able to directly identify the energy of incident gamma rays. In this paper, we propose a method to reconstruct Compton edges in plastic gamma spectra using an artificial neural network for direct pseudo gamma spectroscopy. Spectra simulated using MCNP 6.2 software were used to generate training and validation sets. Our model was trained to reconstruct Compton edges in plastic gamma spectra. In addition, we aimed for our model to be capable of reconstructing Compton edges even for spectra having poor counting statistics by designing a dataset generation procedure. Minimum reconstructible counts for single isotopes were evaluated with metric of mean averaged percentage error as 650 for Co, 2000 for Cs, 3050 for Na, and 3750 for Ba. The performance of our model was verified using the simulated spectra measured by a PVT detector. Although our model was trained using simulation data only, it successfully reconstructed Compton edges even in measured gamma spectra with poor counting statistics.
塑料闪烁体探测器由于其独特的特性而被广泛应用于辐射测量中。然而，由于能量展宽效应和其能谱中没有光峰，它们通常用于计数应用。为了克服它们的弱点，已经有许多关于伪谱的研究报告，但大多数研究都无法直接识别入射伽马射线的能量。在本文中，我们提出了一种使用人工神经网络对塑料伽马谱进行直接伪伽马谱重建的方法。使用 MCNP6.2 软件模拟的光谱用于生成训练集和验证集。我们的模型经过训练，用于重建塑料伽马谱中的康普顿边缘。此外，我们旨在通过设计数据集生成程序，使我们的模型即使在计数统计数据较差的情况下也能够重建康普顿边缘。使用平均百分比误差作为度量标准，对单个同位素的最小可重建计数进行了评估，Co 的最小可重建计数为 650，Cs 的最小可重建计数为 2000，Na 的最小可重建计数为 3050，Ba 的最小可重建计数为 3750。我们的模型使用 PVT 探测器测量的模拟光谱进行了验证。尽管我们的模型仅使用模拟数据进行训练，但它成功地重建了即使在计数统计数据较差的测量伽马光谱中的康普顿边缘。
