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Ground Radioactivity Distribution Reconstruction and Dose Rate Estimation Based on Spectrum Deconvolution
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 groun...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10302513/ https://www.ncbi.nlm.nih.gov/pubmed/37420794 http://dx.doi.org/10.3390/s23125628 |
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author | Xu, Hang Ai, Xianyun Wang, Ying Chen, Wenzhuo Li, Zikun Guan, Xian Wei, Xing Xie, Jianming Chen, Ye |
author_facet | Xu, Hang Ai, Xianyun Wang, Ying Chen, Wenzhuo Li, Zikun Guan, Xian Wei, Xing Xie, Jianming Chen, Ye |
author_sort | Xu, Hang |
collection | PubMed |
description | 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 ((137)Cs) and multi-nuclide ((137)Cs and (60)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. |
format | Online Article Text |
id | pubmed-10302513 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103025132023-06-29 Ground Radioactivity Distribution Reconstruction and Dose Rate Estimation Based on Spectrum Deconvolution Xu, Hang Ai, Xianyun Wang, Ying Chen, Wenzhuo Li, Zikun Guan, Xian Wei, Xing Xie, Jianming Chen, Ye Sensors (Basel) Article 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 ((137)Cs) and multi-nuclide ((137)Cs and (60)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. MDPI 2023-06-15 /pmc/articles/PMC10302513/ /pubmed/37420794 http://dx.doi.org/10.3390/s23125628 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Xu, Hang Ai, Xianyun Wang, Ying Chen, Wenzhuo Li, Zikun Guan, Xian Wei, Xing Xie, Jianming Chen, Ye Ground Radioactivity Distribution Reconstruction and Dose Rate Estimation Based on Spectrum Deconvolution |
title | Ground Radioactivity Distribution Reconstruction and Dose Rate Estimation Based on Spectrum Deconvolution |
title_full | Ground Radioactivity Distribution Reconstruction and Dose Rate Estimation Based on Spectrum Deconvolution |
title_fullStr | Ground Radioactivity Distribution Reconstruction and Dose Rate Estimation Based on Spectrum Deconvolution |
title_full_unstemmed | Ground Radioactivity Distribution Reconstruction and Dose Rate Estimation Based on Spectrum Deconvolution |
title_short | Ground Radioactivity Distribution Reconstruction and Dose Rate Estimation Based on Spectrum Deconvolution |
title_sort | ground radioactivity distribution reconstruction and dose rate estimation based on spectrum deconvolution |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10302513/ https://www.ncbi.nlm.nih.gov/pubmed/37420794 http://dx.doi.org/10.3390/s23125628 |
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