본문 바로가기
KERD
논문KCI 등재

Performance evaluation of a nuclear facility monitoring system using multi-sensor network and artificial intelligence algorithm

2

조회

0

다운로드

0

인용

0

참고문헌

키워드

주제분류원자력공학

초록

As the use of nuclear and radiation technologies increases, the importance of radiation safety and monitoring increases. In this study, we develop a nuclear facility monitoring system (NFMS) for rapid response to radiation accidents in nuclear material storage facilities; (1) multi-sensor network based on NaI(Tl) detector and FPGADAQ system and (2) an artificial neural network (ANN) algorithm for tracking radiation source location. Energy resolution and sensitivity of the detectors were evaluated to accurately track the location of radioactive materials and to identify nuclides using the multi-sensor network. To evaluate the localization accuracy of NFMS, a test storage facility was built and experiments were performed. Localization accuracy was obtained by analyzing the measured counts for each detector using an artificial intelligence (AI) based ANN algorithm, confirming an accuracy of over 99 %. The developed NFMS is expected to contribute to the safe management of radioactive materials in nuclear facilities.

Abstract

As the use of nuclear and radiation technologies increases, the importance of radiation safety and monitoring increases. In this study, we develop a nuclear facility monitoring system (NFMS) for rapid response to radiation accidents in nuclear material storage facilities; (1) multi-sensor network based on NaI(Tl) detector and FPGADAQ system and (2) an artificial neural network (ANN) algorithm for tracking radiation source location. Energy resolution and sensitivity of the detectors were evaluated to accurately track the location of radioactive materials and to identify nuclides using the multi-sensor network. To evaluate the localization accuracy of NFMS, a test storage facility was built and experiments were performed. Localization accuracy was obtained by analyzing the measured counts for each detector using an artificial intelligence (AI) based ANN algorithm, confirming an accuracy of over 99 %. The developed NFMS is expected to contribute to the safe management of radioactive materials in nuclear facilities.

참고문헌 (21)

  1. Pankaj Tandon, "Radiation Safety Guide for Nuclear Medicine Professionals", pp.107~117 (2022), Springer Nature Singapore
  2. Pankaj Tandon, "Radiation Safety Guide for Nuclear Medicine Professionals", pp.119~123 (2022), Springer Nature Singapore
  3. Andrea Chierici, "A high-performance gamma spectrometer for unmanned systems based on off-the-shelf components", Sensors, 22(3), pp.1078~ (2022)
  4. Muhammad Ikmal Ahmad, "Ionizing radiation monitoring technology at the verge of internet of things", Sensors, 21(22), pp.7629~ (2021)
  5. Arfat Ahmad Khan, "A cost-efficient radiation monitoring system for nuclear sites: designing and implementation", Intell. Autom. Soft Comput, 32(3) (2022)
  6. Y. C. Lin, "Real-Time Radiation Monitoring System with Interlock Protection Mechanism in Taiwan Photon Source", ~ (2021)
  7. IAEA Incident and Trafficking Database (ITDB), "International Atomic Energy Agency", IAEA, ~ (2020)
  8. IAEA Nuclear Safety and Security Glossary, Non-serial Publications, "International Atomic Energy Agency", IAEA, ~ (2022)
  9. Zhangfa Yan, "Nuclear radiation detection based on uncovered CMOS camera under dynamic scene", Nucl. Instrum. Methods Phys. Res. Sect. A Accel. Spectrom. Detect. Assoc. Equip, 956, pp.163383~ (2020)
  10. Michael Attas, "Solid State Sensor Arrays and CCD Cameras", pp.287~298 (1996), SPIE
  11. Rudi Van Nieuwenhove, "Nuclear heating measurements by gamma and neutron thermometers", IEEE Trans. Nucl. Sci, 67(9), pp.2073~2080 (2020)
  12. J. J. Stoffel, "Environmental monitoring of Hanford nuclear facility effluents by thermal ionization mass spectrometry", Appl. Spectrosc, 48(11), pp.1326~1330 (1994)
  13. UkJae Lee, "Analysis of the influence of nuclear facilities on environmental radiation by monitoring the highest nuclear power plant density region", Nucl. Eng. Technol, 51(6), pp.1626~1632 (2019)
  14. KA Pradeep Kumar, "Advances in gamma radiation detection systems for emergency radiation monitoring", Nucl. Eng. Technol, 52(10), pp.2151~2161 (2020)
  15. Dennis E. Hadlock, "Thermal limitations of detectors in highlevel radiation fields", Health Phys, 43(1), pp.45~51 (1982)
  16. B. Richard, "Tracking of Weak Radioactive Sources in Crowded Venues", ~ (2009)
  17. Min Kyu Baek, "Design of a nuclear monitoring system based on a multisensor network and artificial intelligence algorithm", Sustainability, 15(7), pp.5915~ (2023)
  18. A. D. Dongare, "Introduction to artificial neural network", Int. J. Eng. Innovat. Technol. (IJEIT), 2(1), pp.189~194 (2012)
  19. Oludare Isaac Abiodun, "State-of-the-art in artificial neural network applications: a survey", Heliyon, pp.e00938~ (2018)
  20. Low-Level Radioactive Waste Repositories: an Analysis of Costs, "Nuclear Energy Agency", OECD, 33~34 (2019)
  21. Hee-Dong Choi, "Basic characterization of uranium by highresolution gamma spectroscopy", Nucl. Eng. Technol, 50(6), pp.929~936 (2018)

관련 논문AI추천

Radionuclide identification method for NaI low-count gamma-ray spectra using artificial neural networkHaijun Fan, Hui Zhao, Jinglun Li, Kun Zhang, Shanqiang Wang, Sheng Qi, Xianyun Ai, Ye Chen한국원자력학회 · Nuclear Engineering and Technology2022 · 제54권 제1호Radionuclide identification based on energy-weighted algorithm and machine learning applied to a multi-array plastic scintillator구본탁, 민철희, 이현철, 전주영, 정희준, 천보위, Yoo Do Hyeon한국원자력학회 · Nuclear Engineering and Technology2023 · 제55권 제10호Time-of-flight based one-dimensional position estimation of radioactive sources using artificial neural network model김승현, 김진홍, 박재형, 송시원, 이봉수, 이상준, 조승현, Cheolhaeng Huh한국원자력학회 · Nuclear Engineering and Technology2025 · 제57권 제9호A novel directional radiation monitoring system for real-time nuclide identification and source localization using DOI method강주완, 백민규, 이성연, 정용현, 정윤수한국원자력학회 · Nuclear Engineering and Technology2025 · 제57권 제10호A counting-time optimization method for artificial neural network (ANN) based gamma-ray spectroscopy고길영, 김원구, 이상호, 조규성, 조문형, 황지성한국원자력학회 · Nuclear Engineering and Technology2024 · 제56권 제7호Improved fast neutron detection using CNN-based pulse shape discrimination서희, 김호동, 윤선광, 이채훈한국원자력학회 · Nuclear Engineering and Technology2023 · 제55권 제11호

이 간행물의 다른 논문 (49건)