Laser flying-spot thermography: an open-access dataset for machine learning and deep learning

K. Helvig; P. Trouvé-Peloux; L. Gaverina; J-M. Roche; B. Abeloos; C. Pradère

doi:10.1117/12.3000481

28 July 2023 Laser flying-spot thermography: an open-access dataset for machine learning and deep learning

K. Helvig, P. Trouvé-Peloux, L. Gaverina, J-M. Roche, B. Abeloos, C. Pradère

Proceedings Volume 12749, Sixteenth International Conference on Quality Control by Artificial Vision; 127491A (2023) https://doi.org/10.1117/12.3000481
Event: Sixteenth International Conference on Quality Control by Artificial Vision, 2023, Albi, France

Abstract

“Flying spot” laser infrared thermography (FST) is a non destructive testing technique able to detect small defects by scanning surfaces with a laser heat source. Defects, such as cracks on metallic parts, are revealed by the disturbance of heat propagation measured by an infrared camera. Deep learning approaches are now very efficient to automatically analyse and use contextual information from data, and can be used for crack detection. However, in the literature only few works deal with the use of deep learning for the crack detection in FST. Indeed obtaining a large amount of data from FST examinations can be expensive and time-consuming. We propose here to build a generic, open-access dataset of laser thermography for defect detection. This database can be used by the community to develop new crack detection methods that can be benchmarked on the same database, as well as for pretraining networks for similar application tasks. We also present results of state of the art detection networks trained with the proposed database. These models give a basis for future works. Dataset, called FLYD (FLYing spot thermography Dataset), will be available in : https://github.com/kevinhelvig/FLYD/.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

K. Helvig, P. Trouvé-Peloux, L. Gaverina, J-M. Roche, B. Abeloos, and C. Pradère "Laser flying-spot thermography: an open-access dataset for machine learning and deep learning", Proc. SPIE 12749, Sixteenth International Conference on Quality Control by Artificial Vision, 127491A (28 July 2023); https://doi.org/10.1117/12.3000481

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