Temporal and spatial deep learning network for infrared thermal defect detection
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 …
detect the inner defects on a complex shaped specimen by using conventional optical …
Sparse principal component thermography for subsurface defect detection in composite products
Active thermography is an efficient and powerful technique for nondestructive testing of
products made of composite materials, which enables rapid inspection of large areas …
products made of composite materials, which enables rapid inspection of large areas …
Independent component thermography for non-destructive testing of defects in polymer composites
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 …
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
In this work, damage sensing and self-healing of carbon fiber polypropylene (CFPP)/carbon
nanotube (CNT) nano-composite were performed based on addressable conducting …
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 …
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
Data analysis methods have been extensively used in active thermography for defect
identification. Among them, principal component thermography (PCT) is popular for …
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 …
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 …
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
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 …
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 …
improved end result from a set of possible inputs. It is considered to be an exceptional …