Jaime Zabalza
Hyperspectral imaging based corrosion detection in nuclear packages.
Zabalza, Jaime; Murray, Paul; Bennett, Stuart; Campbell, Andrew J.; Marshall, Stephen; Ren, Jinchang; Yan, Yijun; Bernard, Robert; Hepworth, Steve; Malone, Simon; Cockbain, Neil; Offin, Douglas; Holliday, Craig
Authors
Paul Murray
Stuart Bennett
Andrew J. Campbell
Stephen Marshall
Professor Jinchang Ren j.ren@rgu.ac.uk
Professor of Computing Science
Dr Yijun Yan y.yan2@rgu.ac.uk
Research Fellow
Robert Bernard
Steve Hepworth
Simon Malone
Neil Cockbain
Douglas Offin
Craig Holliday
Abstract
In the Sellafield nuclear site, intermediate level waste and special nuclear material is stored above ground in stainless steel packages or containers, with thousands expected to be stored for several decades before permanent disposal in a geological disposal facility. During this intermediate storage, the packages are susceptible to corrosion, which can potentially undermine their structural integrity. Therefore, long term monitoring is required. In this work, hyperspectral imaging (HSI) was evaluated as a non-destructive tool for detecting corrosion on stainless steel surfaces. Real samples from Sellafield, including stainless steel 1.4404 (known as 316L) and 2205 plates from the Sellafield atmospheric testing corrosion site, were imaged in the experiments, measuring the spectral responses for corrosion in the visible near-infrared (VNIR, 400-1000 nm) and short-wave-infrared (SWIR, 900-2500 nm) regions. Based on the spectral responses observed, a new concept denoted as Corrosion Index (Ci) was introduced and evaluated to estimate corrosion maps. With the CI, every pixel in the hyperspectral image is given a value between zero and one, aimed at representing corrosion intensity for a given location of the sample. Results suggest that HSI, combined with our proposed CI analysis techniques, could be used for effective automated detection of corrosion in nuclear packages.
Citation
ZABALZA, J., MURRAY, P., BENNETT, S., CAMPBELL, A.J., MARSHALL, S., REN, J., YAN, Y., BERNARD, R., HEPWORTH, S., MALONE, S., COCKBAIN, N., OFFIN, D. and HOLLIDAY, C. 2023. Hyperspectral imaging based corrosion detection in nuclear packages. IEEE sensors journal [online], 23(21), pages 25607-25617. Available from: https://doi.org/10.1109/jsen.2023.3312938
Journal Article Type | Article |
---|---|
Acceptance Date | Sep 18, 2023 |
Online Publication Date | Sep 18, 2023 |
Publication Date | Nov 1, 2023 |
Deposit Date | Oct 12, 2023 |
Publicly Available Date | Oct 12, 2023 |
Journal | IEEE sensors journal |
Print ISSN | 1530-437X |
Electronic ISSN | 1558-1748 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Peer Reviewed | Peer Reviewed |
Volume | 23 |
Issue | 21 |
Pages | 25607-25617 |
DOI | https://doi.org/10.1109/JSEN.2023.3312938 |
Keywords | Corrosion; Hyperspectral imaging; Nuclear packages; Stainless steel; Imaging; Sensors; Steel; Testing; Image color analysis |
Public URL | https://rgu-repository.worktribe.com/output/2107708 |
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