Development of machine learning methods for mechanical problems associated with fibre composite materials: A review

M Liu, H Li, H Zhou, H Zhang, G Huang - Composites Communications, 2024 - Elsevier
Fibre composite materials (FCMs) are widely used in the aerospace, military defence, and
engineering manufacturing industries due to their high strength and high modulus …

Latest advances in common signal processing of pulsed thermography for enhanced detectability: A review

Y Chung, S Lee, W Kim - Applied Sciences, 2021 - mdpi.com
Non-destructive testing (NDT) is a broad group of testing and analysis techniques used in
science and industry to evaluate the properties of a material, structure, or system for …

Deep learning for defect characterization in composite laminates inspected by step-heating thermography

R Marani, D Palumbo, U Galietti, T D'Orazio - Optics and Lasers in …, 2021 - Elsevier
This paper presents a complete procedure for the non-destructive analysis of composite
laminates, taking advantage of the step-heating infrared thermography and the latest …

Introduction of the combination of thermal fundamentals and Deep Learning for the automatic thermographic inspection of thermal bridges and water-related problems …

I Garrido, S Lagüela, Q Fang, P Arias - Quantitative InfraRed …, 2023 - Taylor & Francis
Infrastructure inspection is fundamental to keep its service performance at the highest level.
For that, special attention should be paid to the most severe defects in order to be able to …

A deep learning method for the impact damage segmentation of curve-shaped cfrp specimens inspected by infrared thermography

Z Wei, H Fernandes, HG Herrmann, JR Tarpani… - Sensors, 2021 - mdpi.com
Advanced materials such as continuous carbon fiber-reinforced thermoplastic (CFRP)
laminates are commonly used in many industries, mainly because of their strength, stiffness …

Inline defective laser weld identification by processing thermal image sequences with machine and deep learning techniques

D Buongiorno, M Prunella, S Grossi, SM Hussain… - Applied Sciences, 2022 - mdpi.com
The non-destructive testing methods offer great benefit in detecting and classifying the weld
defects. Among these, infrared (IR) thermography stands out in the inspection …

Automatic detection of CFRP subsurface defects via thermal signals in long pulse and lock-in thermography

X Cheng, P Chen, Z Wu, M Cech… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Thermography is widely used to detect delamination defects in carbon fiber-reinforced
plastics (CFRPs). This article proposes a model to detect defects automatically by extracting …

[HTML][HTML] Machine learning based thermal imaging damage detection in glass-epoxy composite materials

A Sarhadi, RQ Albuquerque, M Demleitner… - Composite …, 2022 - Elsevier
Abstract Machine learning (ML) based fatigue damage detection from thermal imaging in
glass-epoxy composites is an important component of remote structural health monitoring …

Deep transfer learning method for detection of internal cavities in concrete-filled steel tube structural elements

X Su, X Feng, S Gong, F Ansari - Tunnelling and Underground Space …, 2024 - Elsevier
Concrete-filled steel tubes (CFSTs) are widely used as structural elements in civil
engineering. However, their load-carrying capacities are jeopardized due to construction or …

A reliability study on automated defect assessment in optical pulsed thermography

S **ang, AM Omer, M Li, D Yang, A Osman… - Infrared Physics & …, 2023 - Elsevier
Nowadays, the reliability of data analysis and decision-making based on deep learning (DL)
remains a primary concern in promoting DL technology for industrial non-destructive testing …