| Autor: |
Bongsub Song, Jongwon Park, Dongwon Yun |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Nuclear Engineering and Technology, Vol 55, Iss 12, Pp 4695-4702 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1738-5733 |
| DOI: |
10.1016/j.net.2023.08.041 |
| Popis: |
Nuclear power plants play a pivotal role in the global energy infrastructure, fulfilling a substantial share of the world's energy requirements in a sustainable way. The management of these facilities, especially the handling of spent nuclear fuel (SNF), necessitates meticulous inspections to guarantee operational safety and efficiency. However, the prevailing inspection methodologies lean heavily on human operators, which presents challenges due to the potential hazards of the SNF environment. This study introduces the design of a novel Pre-Batched Inspection Strategy (PBIS) that integrates robotic automation and image processing techniques to bolster the inspection process. This methodology deploys robotics to undertake tasks that could be perilous or time-intensive for humans, while image processing techniques are used for precise identification of SNF targets and regulating the robotic system. The implementation of PBIS holds considerable promise in minimizing inspection time and enhancing worker safety. This paper elaborates on the structure, capabilities, and application of PBIS, underlining its potential implications for the future of nuclear energy inspections. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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