Deep learning for structural health monitoring: Data, algorithms, applications, challenges, and trends

J Jia, Y Li - Sensors, 2023 - mdpi.com
Environmental effects may lead to cracking, stiffness loss, brace damage, and other
damages in bridges, frame structures, buildings, etc. Structural Health Monitoring (SHM) …

Pavement crack detection through a deep-learned asymmetric encoder-decoder convolutional neural network

SA Fakhri, M Satari Abrovi, H Zakeri… - … Journal of Pavement …, 2023 - Taylor & Francis
Crack detection on roads' surfaces is an important issue in pavement management, as it
provides an indication of the quality of the road and its deterioration over time. Pavement …

[HTML][HTML] Recent advances in crack detection technologies for structures: a survey of 2022-2023 literature

R Alhajj, H Kaveh - Frontiers in Built Environment, 2024 - frontiersin.org
Cracks, as structural defects or fractures in materials like concrete, asphalt, and metal, pose
significant challenges to the stability and safety of various structures. Addressing crack …

[PDF][PDF] Convolutional neural network for predicting failure type in concrete cylinders during compression testing

JMP Ojeda, BA Cayatopa-Calderón, LQ Huatangari… - Civ Eng J, 2023 - researchgate.net
Cracks in concrete cause structural damage, and it is important to identify and classify them.
The objective of the research was to describe the behavior and predict the type of failure in …

Enhanced concrete crack detection and proactive safety warning based on I-ST-UNet model

H Zhang, L Ma, Z Yuan, H Liu - Automation in Construction, 2024 - Elsevier
Abstracts Existing Swin-Transformer-UNet models for concrete crack detection have several
limitations, such as weak feature extraction and loss of detailed image information. This …

[HTML][HTML] Parametric image-based concrete defect assessment method

DE Lee, G Hong, M Maruthi, CY Yi, YJ Park - Case Studies in …, 2024 - Elsevier
Structural health monitoring aims to ensure the integrity of infrastructure. Assessing
structural integrity through image classification techniques based on human perception is …

Deep recurrent-convolutional neural network learning and physics Kalman filtering comparison in dynamic load identification

M Impraimakis - Structural Health Monitoring, 2024 - journals.sagepub.com
The dynamic structural load identification capabilities of the gated recurrent unit, long short-
term memory, and convolutional neural networks are examined herein. The examination is …

[PDF][PDF] Long-term shape sensing of bridge girders using automated ROI extraction of LiDAR point clouds

GK Geetha, S Lee, J Lee, SH Sim - Smart Structures and Systems, 2024 - researchgate.net
This study discusses the long-term deformation monitoring and shape sensing of bridge
girder surfaces with an automated extraction scheme for point clouds in the Region Of …

Inspection robot and wall surface detection method for coal mine wind shaft

C Tang, E Gao, Y Li, M Li, D Bai, H Tang, G Zhou - Applied Sciences, 2023 - mdpi.com
The coal mine wind shaft is an important ventilation channel in coal mines, and it is of great
significance to ensure its long-term safety. At present, the inspection of wind shafts still …

Reinforced concrete surface cracks length detection and length estimation by using digital image processing approach

SF Senin, A Yusuff, R Rohim… - IOP Conference Series …, 2023 - iopscience.iop.org
Surface cracks are a common failure that occurs in reinforced concrete structures (RC). With
the help of new technologies, access to crack properties should be easier and help the …