Data for: Infrared-Based Damage Detection in Thick Composites via Transfer Learning on Simulated and Experimental Data

Published: 3 October 2025| Version 1 | DOI: 10.17632/xjf5cmkjm3.1
Contributors:
Muyao Li, Davide Leonetti, Donatella Donatella Zappalá, H.H. (Bert) Snijder

Description

Title of the dataset: Data for: Infrared-Based Damage Detection in Thick Composites via Transfer Learning on Simulated and Experimental Data Subfolders: principal_components_epoxy_resin_experiments --> The first 9 principal components extracted from the 28 thermal videos for the resin plates (.npy file) principal_components_GFRP_experiments --> The first 9 principal components extracted from the 7 thermal videos for the GFRP plate (.npy file) GFRP thermal videos --> 7 thermal videos acquired through step-heating thermography tests on a GFRP plate specimen (.mat file) FE models --> 3 ANSYS project archives containing the data of 960 FE models of resin plates (.wbpz file) U-Net --> Python code for the developed U-Net model (.py file) PCT code --> Python code to perform Principal Component Thermography on thermal videos (.py file) Citing both the dataset and the original paper is highly recommended since it promotes reproducibility, gives credit to the full research effort, and helps track impact accurately.

Files

Categories

Artificial Intelligence, Composite Material, Thermography, Delamination

Funders

Licence