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Hyperspectral Imaging based Characterization and Identification of Sintered UO2 Fuel Pellets

Research output: Contribution to conference - Without ISBN/ISSN › Abstract › peer-review

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Hyperspectral Imaging based Characterization and Identification of Sintered UO2 Fuel Pellets. / Zabalza, Jaime; Parker, Andrew; Bandala Sanchez, Manuel et al.
2023. Abstract from 2023 IEEE Nuclear Science Symposium, Vancouver, Canada.

Research output: Contribution to conference - Without ISBN/ISSN › Abstract › peer-review

Harvard

Zabalza, J, Parker, A, Bandala Sanchez, M, Murray, P, Marshall, S, Ma, X, Taylor, CJ & Joyce, M 2023, 'Hyperspectral Imaging based Characterization and Identification of Sintered UO2 Fuel Pellets', 2023 IEEE Nuclear Science Symposium, Vancouver, Canada, 4/11/23 - 11/11/23.

APA

Zabalza, J., Parker, A., Bandala Sanchez, M., Murray, P., Marshall, S., Ma, X., Taylor, C. J., & Joyce, M. (2023). Hyperspectral Imaging based Characterization and Identification of Sintered UO2 Fuel Pellets. Abstract from 2023 IEEE Nuclear Science Symposium, Vancouver, Canada.

Vancouver

Zabalza J, Parker A, Bandala Sanchez M, Murray P, Marshall S, Ma X et al.. Hyperspectral Imaging based Characterization and Identification of Sintered UO2 Fuel Pellets. 2023. Abstract from 2023 IEEE Nuclear Science Symposium, Vancouver, Canada.

Author

Zabalza, Jaime ; Parker, Andrew ; Bandala Sanchez, Manuel et al. / Hyperspectral Imaging based Characterization and Identification of Sintered UO2 Fuel Pellets. Abstract from 2023 IEEE Nuclear Science Symposium, Vancouver, Canada.

Bibtex

@conference{89f3ba3fa9ff4408ab56e9df4249e7c0,
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 HIS technology can be used for the fast-non-invasive characterization and identification of sintered UO2 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.",
author = "Jaime Zabalza and Andrew Parker and {Bandala Sanchez}, Manuel and Paul Murray and Stephen Marshall and Xiandong Ma and Taylor, {C. James} and Malcolm Joyce",
year = "2023",
month = nov,
day = "6",
language = "English",
note = "2023 IEEE Nuclear Science Symposium ; Conference date: 04-11-2023 Through 11-11-2023",

}

RIS

TY - CONF

T1 - Hyperspectral Imaging based Characterization and Identification of Sintered UO2 Fuel Pellets

AU - Zabalza, Jaime

AU - Parker, Andrew

AU - Bandala Sanchez, Manuel

AU - Murray, Paul

AU - Marshall, Stephen

AU - Ma, Xiandong

AU - Taylor, C. James

AU - Joyce, Malcolm

PY - 2023/11/6

Y1 - 2023/11/6

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 HIS technology can be used for the fast-non-invasive characterization and identification of sintered UO2 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 HIS technology can be used for the fast-non-invasive characterization and identification of sintered UO2 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.

M3 - Abstract

T2 - 2023 IEEE Nuclear Science Symposium

Y2 - 4 November 2023 through 11 November 2023

ER -