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Volume 133
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Proceeding Paper

Spatially Resolved Monitoring of the Curing Degree in the Liquid Resin Infusion Process Using Near-Infrared Hyperspectral Imaging †

by
Xabier Zurutuza
1,*,
Laura Arévalo
1,
Janusz Poplawski
1,
Cristian Builes
2,
Mario Román
2,
Tania Grandal
3,
Arantzazu Núñez
3,
Rubén Ruiz
3,
Daniel Maestro-Watson
4 and
Luka Eciolaza
4
1
LORTEK Technological Centre, Basque Research and Technology Alliance (BRTA), Arranomendia Kalea 4A, 20240 Ordizia, Spain
2
Advanced Composites Technologies, R&D Division, AIMEN Technology Centre, Polígono Industrial de Cataboi, Sector 2, Parcela 3, 36418 O Porriño, Spain
3
Smart Systems & Smart Manufacturing, AIMEN Technology Centre, Polígono Industrial de Cataboi, Sector 2, Parcela 3, 36418 O Porriño, Spain
4
Electronics and Computer Science Department, Mondragon Unibertsitatea, Goiru Kalea 2, 20500 Mondragón, Spain
*
Author to whom correspondence should be addressed.
†
Presented at the 15th EASN International Conference, Madrid, Spain, 14–17 October 2025.
Eng. Proc. 2026, 133(1), 72; https://doi.org/10.3390/engproc2026133072
Published: 6 May 2026
(This article belongs to the Proceedings of The 15th EASN International Conference on “Innovation in Aviation & Space Towards Sustainability Today & Tomorrow”)
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Abstract

To ensure consistent quality in composite aerostructures, advanced non-invasive monitoring techniques are needed to detect global and local deviations during manufacturing. This study presents a real-time, spatially resolved method for monitoring the curing stage of Liquid Resin Infusion (LRI) using Near-Infrared Hyperspectral Imaging (NIR-HSI). Unlike traditional point-based tools such as disposable dielectric sensors, NIR-HSI enables full-field, non-contact assessment of the chemical evolution of the resin, providing valuable spatial information for detecting inhomogeneities caused by temperature gradients or uneven resin flow, factors known to affect the final mechanical properties of composites. Previous investigations demonstrated that hyperspectral data acquired during LRI correlate with the degree of cure estimated from a dielectric sensor. In the present study, we extend this analysis through a new experimental campaign designed to validate our earlier findings and strengthen the predictive model. To improve robustness and generalizability, the curing temperature, a key driver of cure kinetics, was systematically varied to introduce controlled changes in cure behavior. This increased variability enhances model reliability and supports more accurate prediction of curing progression under realistic manufacturing conditions.
Keywords: Near-Infrared Hyperspectral Imaging; composite manufacturing; curing state monitoring; Liquid Resin Infusion; chemometrics; machine learning Near-Infrared Hyperspectral Imaging; composite manufacturing; curing state monitoring; Liquid Resin Infusion; chemometrics; machine learning

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MDPI and ACS Style

Zurutuza, X.; Arévalo, L.; Poplawski, J.; Builes, C.; Román, M.; Grandal, T.; Núñez, A.; Ruiz, R.; Maestro-Watson, D.; Eciolaza, L. Spatially Resolved Monitoring of the Curing Degree in the Liquid Resin Infusion Process Using Near-Infrared Hyperspectral Imaging. Eng. Proc. 2026, 133, 72. https://doi.org/10.3390/engproc2026133072

AMA Style

Zurutuza X, Arévalo L, Poplawski J, Builes C, Román M, Grandal T, Núñez A, Ruiz R, Maestro-Watson D, Eciolaza L. Spatially Resolved Monitoring of the Curing Degree in the Liquid Resin Infusion Process Using Near-Infrared Hyperspectral Imaging. Engineering Proceedings. 2026; 133(1):72. https://doi.org/10.3390/engproc2026133072

Chicago/Turabian Style

Zurutuza, Xabier, Laura Arévalo, Janusz Poplawski, Cristian Builes, Mario Román, Tania Grandal, Arantzazu Núñez, Rubén Ruiz, Daniel Maestro-Watson, and Luka Eciolaza. 2026. "Spatially Resolved Monitoring of the Curing Degree in the Liquid Resin Infusion Process Using Near-Infrared Hyperspectral Imaging" Engineering Proceedings 133, no. 1: 72. https://doi.org/10.3390/engproc2026133072

APA Style

Zurutuza, X., Arévalo, L., Poplawski, J., Builes, C., Román, M., Grandal, T., Núñez, A., Ruiz, R., Maestro-Watson, D., & Eciolaza, L. (2026). Spatially Resolved Monitoring of the Curing Degree in the Liquid Resin Infusion Process Using Near-Infrared Hyperspectral Imaging. Engineering Proceedings, 133(1), 72. https://doi.org/10.3390/engproc2026133072

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