Temporal and spatial deep learning network for infrared thermal defect detection

Q Luo, B Gao, WL Woo, Y Yang - Ndt & E International, 2019 - Elsevier
Most common types of defects for composite are debond and delamination. It is difficult to
detect the inner defects on a complex shaped specimen by using conventional optical …

Sparse principal component thermography for subsurface defect detection in composite products

JY Wu, S Sfarra, Y Yao - IEEE transactions on industrial …, 2018 - ieeexplore.ieee.org
Active thermography is an efficient and powerful technique for nondestructive testing of
products made of composite materials, which enables rapid inspection of large areas …

Independent component thermography for non-destructive testing of defects in polymer composites

Y Liu, JY Wu, K Liu, HL Wen, Y Yao… - Measurement …, 2019 - iopscience.iop.org
Thermographic data processing and analysis is critical for effective infrared thermography
non-destructive testing of defects in composite materials. In this research work, the concept …

Damage detection and self-healing of carbon fiber polypropylene (CFPP)/carbon nanotube (CNT) nano-composite via addressable conducting network

SJ Joo, MH Yu, WS Kim, HS Kim - Composites Science and Technology, 2018 - Elsevier
In this work, damage sensing and self-healing of carbon fiber polypropylene (CFPP)/carbon
nanotube (CNT) nano-composite were performed based on addressable conducting …

Employing a U-net convolutional neural network for segmenting impact damages in optical lock-in thermography images of CFRP plates

BCF Oliveira, AA Seibert, VK Borges… - Nondestructive …, 2021 - Taylor & Francis
Carbon fibre reinforced plastics (CFRPs) are replacing metals in fields such as aerospace
due to their high mechanical strength and low weight. They have an anisotropic behaviour …

Thermographic data analysis for defect detection by imposing spatial connectivity and sparsity constraints in principal component thermography

CM Wen, S Sfarra, G Gargiulo… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Data analysis methods have been extensively used in active thermography for defect
identification. Among them, principal component thermography (PCT) is popular for …

Thermal wave image deblurring based on depth residual network

H Jiang, F Chen, X Liu, J Chen, K Zhang… - Infrared Physics & …, 2021 - Elsevier
Thermal wave imaging is a nondestructive testing (NDT) technology widely used to detect
defects for various materials. It is important for quality control purposes to be able to clearly …

Comparison of Unet and Mask R-CNN for impact damage segmentation in lock-in thermography phase images

PG Minatel, BCF de Oliveira… - … Visual Inspection and …, 2021 - spiedigitallibrary.org
Carbon fiber reinforced plastic (CFRPs) is a composite material that has substituted metal
alloys in many industrial fields. Non-destructive testing techniques are interesting inspection …

A convolution residual network for heating-invariant defect segmentation in composite materials inspected by lock-in thermography

D Morelli, R Marani, E D'Accardi… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
This article proposes an automatic approach for segmenting inclusion defects in composite
materials inspected by lock-in thermography (LT) in a heat source invariant way. In the …

An Effective Surface Defect Detection Method Using Adaptive Thresholding Fused With PSO Algorithm.

Y Aslam, N Santhi, N Ramasamy… - International Journal of …, 2018 - search.ebscohost.com
In Image processing and computer vision, the optimization technique aims at producing
improved end result from a set of possible inputs. It is considered to be an exceptional …