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基于谱解卷积的地面放射性分布重建和剂量率估算。

Ground Radioactivity Distribution Reconstruction and Dose Rate Estimation Based on Spectrum Deconvolution.

机构信息

State Key Laboratory of NBC Protection for Civilian, Beijing 102205, China.

Nuclear Technology Key Laboratory of Earth Science in Sichuan, Chengdu University of Technology, Chengdu 610059, China.

出版信息

Sensors (Basel). 2023 Jun 15;23(12):5628. doi: 10.3390/s23125628.

Abstract

Estimating the gamma dose rate at one meter above ground level and determining the distribution of radioactive pollution from aerial radiation monitoring data are the core technical issues of unmanned aerial vehicle nuclear radiation monitoring. In this paper, a reconstruction algorithm of the ground radioactivity distribution based on spectral deconvolution was proposed for the problem of regional surface source radioactivity distribution reconstruction and dose rate estimation. The algorithm estimates unknown radioactive nuclide types and their distributions using spectrum deconvolution and introduces energy windows to improve the accuracy of the deconvolution results, achieving accurate reconstruction of multiple continuous distribution radioactive nuclides and their distributions, as well as dose rate estimation of one meter above ground level. The feasibility and effectiveness of the method were verified through cases of single-nuclide (Cs) and multi-nuclide (Cs and Co) surface sources by modeling and solving them. The results showed that the cosine similarities between the estimated ground radioactivity distribution and dose rate distribution with the true value were 0.9950 and 0.9965, respectively, which could prove that the proposed reconstruction algorithm would effectively distinguish multiple radioactive nuclides and accurately restore their radioactivity distribution. Finally, the influences of statistical fluctuation levels and the number of energy windows on the deconvolution results were analyzed, showing that the lower the statistical fluctuation level and the more energy window divisions, the better the deconvolution results.

摘要

估算距地面一米处的伽马剂量率,并根据空中辐射监测数据确定放射性污染的分布,是无人机核辐射监测的核心技术问题。针对区域面源放射性分布重建和剂量率估算问题,本文提出了一种基于谱反卷积的地面放射性分布重建算法。该算法利用谱反卷积估计未知放射性核素类型及其分布,并引入能量窗以提高反卷积结果的准确性,从而实现对多个连续分布放射性核素及其分布的精确重建,以及距地面一米处的剂量率估算。通过对单核素(Cs)和面源多核素(Cs 和 Co)进行建模和求解,验证了该方法的可行性和有效性。结果表明,估计的地面放射性分布和剂量率分布与真值的余弦相似度分别为 0.9950 和 0.9965,这证明了所提出的重建算法能够有效地区分多种放射性核素,并准确地恢复其放射性分布。最后,分析了统计波动水平和能量窗数量对反卷积结果的影响,表明统计波动水平越低,能量窗划分越多,反卷积结果越好。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6585/10302513/8dbab4dda176/sensors-23-05628-g024.jpg

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