Hyperspectral imaging based characterization and identification of sintered UO2 fuel pellets

Jaime Zabalza; A.J. Parker; M. Bandala; R. David Dunphy; Paul Murray; Stephen Marshall; X. Ma; C.J. Taylor; M. Joyce; N. Cockbain; D. F.  Lee; P. Chard; D. Hutchinson; P. Stirzaker; D. Eaves

doi:10.1109/NSSMICRTSD49126.2023.10338358

Hyperspectral imaging based characterization and identification of sintered UO2 fuel pellets

Jaime Zabalza, A.J. Parker, M. Bandala, R. David Dunphy, Paul Murray, Stephen Marshall, X. Ma, C.J. Taylor, M. Joyce, N. Cockbain, D. F. Lee, P. Chard, D. Hutchinson, P. Stirzaker, D. Eaves

Electronic And Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

Abstract

Hyperspectral Imaging (HSI) is a well-established technology able to capture the same spatial scene or image in hundreds of different wavelengths across the electromagnetic spectrum, covering not only the visible but also the shortwave infrared range (1000-2500nm), potentially revealing information otherwise invisible to the human eye. In this work, we explored whether HSI technology can be used for the fast-non-invasive characterization and identification of sintered UO 2 fuel pellets. Preliminary experiments included the imaging of the pellets, revealing their spectral responses. These show promising features that could be used for their identification, where two different groups of pellets, pure and doped, seem to be easily recognized based on their spectral response. The experiments included a pixel-wise classification map generated via the Spectral Angle Mapper (SAM) technique in which the pure and doped pellets are successfully identified.

Original language	English
Title of host publication	2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)
Publisher	IEEE
ISBN (Electronic)	979-8-3503-3866-9
ISBN (Print)	979-8-3503-3867-6
DOIs	https://doi.org/10.1109/NSSMICRTSD49126.2023.10338358
Publication status	Published - 13 Dec 2023
Event	IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector (RTSD) - Vancouver, Canada Duration: 4 Nov 2023 → 11 Nov 2023

Publication series

Name	2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)
Publisher	IEEE
ISSN (Print)	1082-3654
ISSN (Electronic)	2577-0829

Conference

Conference	IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector (RTSD)
Country/Territory	Canada
City	Vancouver
Period	4/11/23 → 11/11/23

Keywords

hyperspectral imaging
UO2 fuel pellets

Access to Document

10.1109/NSSMICRTSD49126.2023.10338358

Cite this

Zabalza, J., Parker, A. J., Bandala, M., Dunphy, R. D., Murray, P., Marshall, S., Ma, X., Taylor, C. J., Joyce, M., Cockbain, N., Lee, D. F., Chard, P., Hutchinson, D., Stirzaker, P., & Eaves, D. (2023). Hyperspectral imaging based characterization and identification of sintered UO2 fuel pellets. In 2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD) (2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)). IEEE. https://doi.org/10.1109/NSSMICRTSD49126.2023.10338358

Zabalza, Jaime ; Parker, A.J. ; Bandala, M. et al. / Hyperspectral imaging based characterization and identification of sintered UO2 fuel pellets. 2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD). IEEE, 2023. (2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)).

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title = "Hyperspectral imaging based characterization and identification of sintered UO2 fuel pellets",

abstract = "Hyperspectral Imaging (HSI) is a well-established technology able to capture the same spatial scene or image in hundreds of different wavelengths across the electromagnetic spectrum, covering not only the visible but also the shortwave infrared range (1000-2500nm), potentially revealing information otherwise invisible to the human eye. In this work, we explored whether HSI technology can be used for the fast-non-invasive characterization and identification of sintered UO 2 fuel pellets. Preliminary experiments included the imaging of the pellets, revealing their spectral responses. These show promising features that could be used for their identification, where two different groups of pellets, pure and doped, seem to be easily recognized based on their spectral response. The experiments included a pixel-wise classification map generated via the Spectral Angle Mapper (SAM) technique in which the pure and doped pellets are successfully identified.",

keywords = "hyperspectral imaging, UO2 fuel pellets",

author = "Jaime Zabalza and A.J. Parker and M. Bandala and Dunphy, {R. David} and Paul Murray and Stephen Marshall and X. Ma and C.J. Taylor and M. Joyce and N. Cockbain and Lee, {D. F.} and P. Chard and D. Hutchinson and P. Stirzaker and D. Eaves",

year = "2023",

month = dec,

day = "13",

doi = "10.1109/NSSMICRTSD49126.2023.10338358",

language = "English",

isbn = "979-8-3503-3867-6",

series = "2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)",

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booktitle = "2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)",

note = "IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector (RTSD) ; Conference date: 04-11-2023 Through 11-11-2023",

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Zabalza, J, Parker, AJ, Bandala, M, Dunphy, RD , Murray, P , Marshall, S, Ma, X, Taylor, CJ, Joyce, M, Cockbain, N, Lee, DF, Chard, P, Hutchinson, D, Stirzaker, P & Eaves, D 2023, Hyperspectral imaging based characterization and identification of sintered UO2 fuel pellets. in 2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD). 2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD), IEEE, IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector (RTSD), Vancouver, Canada, 4/11/23. https://doi.org/10.1109/NSSMICRTSD49126.2023.10338358

Hyperspectral imaging based characterization and identification of sintered UO2 fuel pellets. / Zabalza, Jaime; Parker, A.J.; Bandala, M. et al.
2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD). IEEE, 2023. (2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

TY - GEN

T1 - Hyperspectral imaging based characterization and identification of sintered UO2 fuel pellets

AU - Zabalza, Jaime

AU - Parker, A.J.

AU - Bandala, M.

AU - Dunphy, R. David

AU - Murray, Paul

AU - Marshall, Stephen

AU - Ma, X.

AU - Taylor, C.J.

AU - Joyce, M.

AU - Cockbain, N.

AU - Lee, D. F.

AU - Chard, P.

AU - Hutchinson, D.

AU - Stirzaker, P.

AU - Eaves, D.

PY - 2023/12/13

Y1 - 2023/12/13

N2 - Hyperspectral Imaging (HSI) is a well-established technology able to capture the same spatial scene or image in hundreds of different wavelengths across the electromagnetic spectrum, covering not only the visible but also the shortwave infrared range (1000-2500nm), potentially revealing information otherwise invisible to the human eye. In this work, we explored whether HSI technology can be used for the fast-non-invasive characterization and identification of sintered UO 2 fuel pellets. Preliminary experiments included the imaging of the pellets, revealing their spectral responses. These show promising features that could be used for their identification, where two different groups of pellets, pure and doped, seem to be easily recognized based on their spectral response. The experiments included a pixel-wise classification map generated via the Spectral Angle Mapper (SAM) technique in which the pure and doped pellets are successfully identified.

AB - Hyperspectral Imaging (HSI) is a well-established technology able to capture the same spatial scene or image in hundreds of different wavelengths across the electromagnetic spectrum, covering not only the visible but also the shortwave infrared range (1000-2500nm), potentially revealing information otherwise invisible to the human eye. In this work, we explored whether HSI technology can be used for the fast-non-invasive characterization and identification of sintered UO 2 fuel pellets. Preliminary experiments included the imaging of the pellets, revealing their spectral responses. These show promising features that could be used for their identification, where two different groups of pellets, pure and doped, seem to be easily recognized based on their spectral response. The experiments included a pixel-wise classification map generated via the Spectral Angle Mapper (SAM) technique in which the pure and doped pellets are successfully identified.

KW - hyperspectral imaging

KW - UO2 fuel pellets

U2 - 10.1109/NSSMICRTSD49126.2023.10338358

DO - 10.1109/NSSMICRTSD49126.2023.10338358

M3 - Conference contribution book

SN - 979-8-3503-3867-6

T3 - 2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)

BT - 2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)

PB - IEEE

T2 - IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector (RTSD)

Y2 - 4 November 2023 through 11 November 2023

ER -

Zabalza J, Parker AJ, Bandala M, Dunphy RD , Murray P , Marshall S et al. Hyperspectral imaging based characterization and identification of sintered UO2 fuel pellets. In 2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD). IEEE. 2023. (2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)). doi: 10.1109/NSSMICRTSD49126.2023.10338358

Hyperspectral imaging based characterization and identification of sintered UO2 fuel pellets

Abstract

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