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김건(Geon Kim),여도엽(Doyeob Yeo),최유락(Yurak Choi),이종혁(JongHyunk Lee),배지훈(Ji-Hoon Bae) 한국정보기술학회 2021 Proceedings of KIIT Conference Vol.2021 No.11
본 논문은 기계잡음이나 소음환경으로 인해 미세 누출의 진위 판별의 한계를 극복하기 위해 서포트 벡터 머신 기법을 이용한 분석 방법을 제안한다. 제안하는 분석 방법은 플랜트 배관계의 저전력 센서 모듈에서 수집한 미세 누출에 대한 데이터를 사용한다. 본 연구의 실험결과에 따르면, 제안된 구현 모델이 누출 발생 신호가 매우 미약하더라도 95% 이상의 높은 정확도로 누출 판별을 수행할 수 있음을 실험적으로 관찰하였다. In this paper, we propose a support vector machine model to overcome the limitations of determining the authenticity of low-level leakage due to machine noise or noise environment. The proposed analysis method uses data on microleakage collected from the low-power sensor module of the plant piping system. According to the experimental results of this study, it was experimentally observed that the proposed implementation model could perform leak detection with high accuracy of 95% or more even if the leak occurrence signal is very low-level.
Junyoung Lee,Sehoon Choi,Goeun Lee,Doyeob Kim,Chan Hyoeng Kim 한국방사성폐기물학회 2022 한국방사성폐기물학회 학술논문요약집 Vol.20 No.1
During decommissioning of a nuclear power plant, a large amount of radioactive waste is produced, and it is known to cost more than 300 billion won to dispose the waste. To reduce the disposal cost, it is essential to minimize the number of radioactive waste drums, which can be achieved by detecting and removing hotspot contaminations in the radioactive waste drums. Therefore, a Compton CT system for radioactive waste monitoring is under development, which provides the images of both the internal structure of the drum and the radioactive hotspot(s) in the drum. Based on the acquired information, the activity of hotspots can be estimated. The performance of the system is affected by various geometry factors. Therefore, it is essential to determine optimal configuration by evaluating the effects of the factors on the performance of the system. In the present study, we determined the optimum value of the factors and then predicted the performance of the optimized system by using a simulator based on the Geant4 Monte Carlo simulation. For optimization, the factors were evaluated in terms of structural similarity index measure (SSIM) and measurement time. The considered factors were the activity of the CT source, source to object distance (SOD), object to detector distance (ODD), and projection angle. The simulation result showed that the activities of the CT sources were determined as 23 mCi for 137Cs and 9.6 mCi for 60Co. The optimal SOD and ODD were 180 cm and 40 cm, respectively. The optimal projection angle was evaluated as 4° since it achieves the SSIM of 0.95 faster than other projection angles. With the optimized parameters, the performance of the system was evaluated using the IAEA gamma CT standard phantom containing a hotspot of 137Cs (7.02 μCi). The Compton image was reconstructed using the back-projection algorithm, and the CT image was reconstructed using the filtered back-projection algorithm. The result showed that the location of the hotspot in the Compton image was well identified at the true position. The acquired CT image also well represented the internal structure of the phantom, and the estimated mean linear attenuation coefficient value (μ= 0.0789 cm?1) of the phantom was close to the true value (μ= 0.0752 cm?1). In addition, the hotspot activity estimated by combining the information of the Compton image and CT image was 8.06 μCi. Hence, it was found that the Compton CT system provides essential information for radioactive waste drums.