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Hyperspectral Imaging based Detection of PVC during Sellafield Repackaging Procedures
Traditionally, Special Nuclear Material (SNM) at Sellafield has been stored in multi-layered packages, consisting of metallic cans and an over-layer of plasticized Polyvinyl Chloride (PVC) as an intermediate layer when transitioning between areas of different radiological classification. However, it...
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Published in: | IEEE sensors journal 2023-01, Vol.23 (1), p.1-1 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Traditionally, Special Nuclear Material (SNM) at Sellafield has been stored in multi-layered packages, consisting of metallic cans and an over-layer of plasticized Polyvinyl Chloride (PVC) as an intermediate layer when transitioning between areas of different radiological classification. However, it has been found that plasticized PVC can break down in the presence of both radiation and heat, releasing hydrochloric acid which can corrode these metallic containers. Therefore, internal repackaging procedures at Sellafield have focused recently on the removal of these PVC films from containers, where as much degraded and often adhered PVC as possible is manually removed based on visual inspection. This manual operation is time-consuming and it is possible that residual fragments of PVC could remain, leading to corrosion-related issues in future. In this work, Hyperspectral Imaging (HSI) was evaluated as a new tool for detecting PVC on metallic surfaces. Samples of stainless steel type 1.4404 - also known as 316L, the same as is used to construct SNM cans - and PVC were imaged in our experiments, and Support Vector Machine (SVM) classification models were used to generate detection maps. In these maps, pixels were classified into either PVC or 316L based on their spectral responses in the range 954-1700nm of the electromagnetic spectrum. Results suggest that HSI could be used for an effective automated detection and quantification of PVC during repackaging procedures, detection and quantification that could be extended to other similar applications. |
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ISSN: | 1530-437X 1558-1748 |
DOI: | 10.1109/JSEN.2022.3221680 |