[HTML][HTML] Steel crack depth estimation based on 2D images using artificial neural networks

YS Mohamed, HM Shehata, M Abdellatif… - Alexandria Engineering …, 2019 - Elsevier
Automatic crack detection is needed to reduce cost and to improve quality of surface
inspection that is needed for maintenance of infrastructures. In this research, a novel system …

Can we obtain the internal information of a surface crack from Rayleigh waves?

D Wang, J Tang - NDT & E International, 2022 - Elsevier
In this study, the Rayleigh wave responses of surface cracks with irregular planes are
investigated utilizing novel numerical approaches. The effects of the equivalent width, filling …

[PDF][PDF] Evaluation of spalling in bridges using machine vision method

EM Abdelkader, O Moselhi, M Marzouk… - ISARC. Proceedings of …, 2020 - researchgate.net
The growing number of bridges and their deteriorated conditions on one hand and the
budget squeeze for their repair and rehabilitation on the other call for automated detection of …

Crack detection based on attention mechanism with YOLOv5

ML Lan, D Yang, SX Zhou, Y Ding - Engineering Reports, 2024 - Wiley Online Library
In order to reduce the manual workload and reduce the maintenance cost, it is particularly
important to realize automatic detection of cracks. Aiming at the problems of poor real‐time …

Forward and backward mixed-mode crack estimation using artificial neural network

A Khademalrasoul, Z Hatampour… - International Journal of …, 2022 - emerald.com
Purpose In this manuscript, the authors aimed to demonstrate the influences of influential
parameters in mixed-mode crack propagation phenomenon. The authors attempted to cover …

Material Model Calibration of Fiber Reinforced Concrete Using Deep Neural Network

Y Yaşayanlar - 2023 - search.proquest.com
The numerical modeling of fiber reinforced concrete (FRC) structures is quite challenging
due to the material's heterogeneous and anisotropic nature. The majority of material models …