Hybrid deep convolutional networks for the autonomous damage diagnosis of laminated composite structures
This article presents a robust autonomous damage diagnosis method using hybrid deep
convolutional networks for the damage diagnosis of laminated composite structures …
convolutional networks for the damage diagnosis of laminated composite structures …
Noise robust damage detection of laminated composites using multichannel wavelet-enhanced deep learning model
MM Azad, HS Kim - Engineering Structures, 2025 - Elsevier
This paper presents a noise-robust damage detection framework for composite structures
via a commonly used vibration-based non-destructive testing (NDT) method. Recently, deep …
via a commonly used vibration-based non-destructive testing (NDT) method. Recently, deep …
[HTML][HTML] Autonomous data-driven delamination detection in laminated composites with limited and imbalanced data
MM Azad, S Kim, HS Kim - Alexandria Engineering Journal, 2024 - Elsevier
This study addresses the challenges of data scarcity and class imbalance in structural health
monitoring (SHM) of composite structures. Data-driven SHM techniques that benefit from …
monitoring (SHM) of composite structures. Data-driven SHM techniques that benefit from …
Neural networks modeling of strain energy density and Tsai-Wu index in laminated composites
E Ledesma-Orozco, JC Galvis-Chacón… - Journal of …, 2024 - journals.sagepub.com
In laminated composite materials design, optimization mainly targets the stacking sequence
configuration, which is defined by the lamina thickness and fiber orientations within each …
configuration, which is defined by the lamina thickness and fiber orientations within each …