통합 검색 | Korea Science

Deep-learning-based system-scale diagnosis of a nuclear power plant with multiple infrared cameras

Ik Jae Jin;Do Yeong Lim;In Cheol Bang
- Nuclear Engineering and Technology
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- 제55권2호
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- pp.493-505
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- 2023
Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify system conditions using compact Raspberry Pi and IR sensors. This diagnostic technology can identify the presence of an abnormality or accident in whole system, and when an accident occurs, the type of accident and the location of the abnormality can be identified in real-time. For technology development, the experiment for the thermal image measurement and performance validation of major components at each accident condition of NPPs was conducted using a thermal-hydraulic integral effect test facility with compact infrared sensor modules. These thermal images were used for training of deep-learning model, convolutional neural networks (CNN), which is effective for image processing. As a result, a proposed novel diagnostic was developed that can perform diagnosis of components, whole system and accident classification using thermal images. The optimal model was derived based on the modern CNN model and performed prompt and accurate condition monitoring of component and whole system diagnosis, and accident classification. This diagnostic technology is expected to be applied to comprehensive condition monitoring of nuclear power plants for safety.
https://doi.org/10.1016/j.net.2022.10.012 인용 PDF

Irradiation Effect on Silo Dry Storage Systems for CANDU Spent Nuclear Fuel

Taehyung Na;Yeji Kim;Donghee Lee;Taehyeon Kim;Sunghwan Chung
- 방사성폐기물학회지
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- 제22권2호
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- pp.117-128
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- 2024
The 300 concrete silo systems installed and operated at the site of Wolsong nuclear power plant (NPP) have been storing CANDU spent nuclear fuel (SNF) under dry conditions since 1992. The dry storage system must be operated safely until SNF is delivered to an interim storage facility or final repository located outside the NPP in accordance with the SNF management policy of the country. The silo dry storage system consists of a concrete structure, liner steel plate in the inner cavity, and fuel basket. Because the components of the silo system are exposed to high energy radiation owing to the high radioactivity of SNF inside, the effects of irradiation during long-term storage must be analyzed. To this end, material specimens of each component were manufactured and subjected to irradiation and strength tests, and mechanical characteristics before and after irradiation were examined. Notably, the mechanical characteristics of the main components of the silo system were affected by irradiation during the storage of spent fuel. The test results will be used to evaluate the long-term behavior of silo systems in the future.
https://doi.org/10.7733/jnfcwt.2024.013 인용 PDF