A systematic review of convolutional neural network-based structural condition assessment techniques

S Sony, K Dunphy, A Sadhu, M Capretz - Engineering Structures, 2021 - Elsevier
With recent advances in non-contact sensing technology such as cameras, unmanned aerial
and ground vehicles, the structural health monitoring (SHM) community has witnessed a …

Machine vision-based surface crack analysis for transportation infrastructure

W Hu, W Wang, C Ai, J Wang, W Wang, X Meng… - Automation in …, 2021 - Elsevier
Cracks undermine the structural health of transportation infrastructure. Machine vision-
based surface crack analysis is to process infrastructure inspection data collected by …

CrackU‐net: A novel deep convolutional neural network for pixelwise pavement crack detection

J Huyan, W Li, S Tighe, Z Xu… - Structural Control and …, 2020 - Wiley Online Library
Periodic road crack monitoring is an essential procedure for effective pavement
management. Highly efficient and accurate crack measurements are key research topics in …

The failure of edge-cracked hard roof in underground mining: An analytical study

S Ji, X Lai, F Cui, Y Liu, R Pan, J Karlovšek - International Journal of Rock …, 2024 - Elsevier
Hard roof is the primary concern of strata control in underground mining. Various techniques
have been utilized to fracture the hard roof and control the failure of strata. Understanding …

Chipless RFID sensor tag for metal crack detection and characterization

AMJ Marindra, GY Tian - IEEE Transactions on Microwave …, 2018 - ieeexplore.ieee.org
Chipped radio-frequency identification (RFID) sensor systems have been studied for
structural health monitoring (SHM) applications. However, the use of chip in sensor tags and …

Overview of researches on the nondestructive testing method of metal magnetic memory: Status and challenges

P Shi, S Su, Z Chen - Journal of Nondestructive Evaluation, 2020 - Springer
More than 20 years of research progress regarding the nondestructive testing method of
metal magnetic memory is reviewed and summarized in detail. Consequently, this overview …

Deep active learning for civil infrastructure defect detection and classification

C Feng, MY Liu, CC Kao, TY Lee - Computing in civil engineering …, 2017 - ascelibrary.org
Automatic detection and classification of defects in infrastructure surface images can largely
boost its maintenance efficiency. Given enough labeled images, various supervised learning …

[HTML][HTML] TOPO-Loss for continuity-preserving crack detection using deep learning

BG Pantoja-Rosero, D Oner, M Kozinski… - … and Building Materials, 2022 - Elsevier
We present a method for segmenting cracks in images of masonry buildings damaged by
earthquakes. Existing methods of crack detection fail to preserve the continuity of cracks …

Detection of surface cracks in metals using microwave and millimeter-wave nondestructive testing techniques—a review

MA Abou-Khousa, MSU Rahman… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Integrity assessment of metallic structures requires inspection tools capable of detecting and
evaluating cracks reliably. To this end, many microwave and millimeter-wave nondestructive …

[HTML][HTML] Free vibrations of cracked functionally graded graphene platelets reinforced Timoshenko beams based on Hu-Washizu-Barr variational method

K Yee, HB Khaniki, MH Ghayesh, CT Ng - Engineering Structures, 2023 - Elsevier
In this paper, a new theoretical approach is presented for modelling the free vibrations of
functionally graded (FG) graphene platelets (GPL) reinforced thick beams with a single-edge …