@inproceedings{cd1e75a5061d4c1c8fd4031154d2c6f4,
title = "A prototype multi-instrument quality assurance system for responsive nuclear fuel manufacturing",
abstract = "A prototype apparatus for in line quality control assessment of sintered uranium dioxide fuel pellets has been demonstrated. In this work we combine γ-ray spectrometer, laser profilometer, and hyperspectral and RGB cameras in a single system. The combination of instruments provides analytical data on uranium enrichment, pellet geometry, physical defects, and potential chemical contamination. The images and spectra are analyzed using a convolutional neural network and an automated quality control decision taken. The prototype was deployed at the National Nuclear Laboratory, Preston site to analyze Advanced Gas Cooled sintered UO 2 pellets. Results from the pellet analysis are added automatically to a pellet data library for future nuclear security and safeguards auditing and model-training to improve quality assurance decision-making.",
keywords = "convolutional neural network, hyperspectral, combination of instruments, physical defects, uranium enrichment, nuclear security",
author = "A. Parker and M. Bandala and P. Chard and N. Cockbain and D. Dunphy and D. Eaves and D. Hutchinson and X. Ma and S. Marshall and P. Murray and P. Stirzaker and J. Taylor and J. Zabalza and M. Joyce",
year = "2024",
month = sep,
day = "25",
doi = "10.1109/nss/mic/rtsd57108.2024.10656207",
language = "English",
isbn = "9798350388169",
series = "IEEE Symposium on Nuclear Science (NSS/MIC)",
publisher = "IEEE",
booktitle = "2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD)",
note = "2024 IEEE Nuclear Science Symposium, Medical Imaging Conference, and Room-Temperature Semiconductor Detectors Symposium, 2024 NSS MIC RTSD ; Conference date: 26-10-2024 Through 02-11-2024",
}