[HTML][HTML] Abnormal data detection for structural health monitoring: State-of-the-art review

Y Deng, Y Zhao, H Ju, TH Yi, A Li - Developments in the Built Environment, 2024 - Elsevier
Structural health monitoring (SHM) is widely used to monitor and assess the condition and
performance of engineering structures such as, buildings, bridges, dams, and tunnels …

A literature review: Generative adversarial networks for civil structural health monitoring

F Luleci, FN Catbas, O Avci - Frontiers in Built Environment, 2022 - frontiersin.org
Structural Health Monitoring (SHM) of civil structures has been constantly evolving with
novel methods, advancements in data science, and more accessible technology to address …

Point cloud and machine learning-based automated recognition and measurement of corrugated pipes and rebars for large precast concrete beams

J Shu, X Zhang, W Li, Z Zeng, H Zhang… - Automation in …, 2024 - Elsevier
It is important for quality inspection to quickly identify the correctness of the installation
position of corrugated pipes and rebars on construction site. A point clouds and machine …

DF-CDM: Conditional diffusion model with data fusion for structural dynamic response reconstruction

J Shu, H Yu, G Liu, Y Duan, H Hu, H Zhang - Mechanical Systems and …, 2025 - Elsevier
In structural health monitoring (SHM) systems, data loss inevitably occurs and reduces the
applicability of SHM techniques, such as condition assessment and damage identification …

[HTML][HTML] Concrete and steel bridge Structural Health Monitoring—Insight into choices for machine learning applications

D Xu, X Xu, MC Forde, A Caballero - Construction and Building Materials, 2023 - Elsevier
Abstract Structural Health Monitoring (SHM) systems have been installed on bridges across
the world at an increasing rate in recent years, providing vital data for bridge assessment …

[HTML][HTML] Footbridge damage detection using smartphone-recorded responses of micromobility and convolutional neural networks

Z Li, Y Lan, W Lin - Automation in Construction, 2024 - Elsevier
This paper presents a footbridge damage detection and classification framework using
smartphone-recorded responses of micromobility and deep learning techniques. Time …

A multi-task learning-based automatic blind identification procedure for operational modal analysis

J Shu, C Zhang, Y Gao, Y Niu - Mechanical Systems and Signal Processing, 2023 - Elsevier
Traditional modal analysis approaches for structural heath monitoring (SHM) have a low
implementation efficiency. This study develops an artificial intelligence (AI)-based automatic …

The application of deep learning in bridge health monitoring: A literature review

GQ Zhang, B Wang, J Li, YL Xu - Advances in Bridge Engineering, 2022 - Springer
Along with the advancement in sensing and communication technologies, the explosion in
the measurement data collected by structural health monitoring (SHM) systems installed in …

Point cloud-based dimensional quality assessment of precast concrete components using deep learning

J Shu, W Li, C Zhang, Y Gao, Y **ang, L Ma - Journal of Building …, 2023 - Elsevier
The dimensional quality of precast concrete (PC) subcomponents (concrete and rebars)
should be inspected in advance to ensure assembly quality. Currently, PC components are …

Model-informed deep learning strategy with vision measurement for damage identification of truss structures

J Shu, C Zhang, X Chen, Y Niu - Mechanical Systems and Signal …, 2023 - Elsevier
Structural damage identification approaches can be divided into two categories, ie data-
driven approaches via statistical pattern recognition and model-based approaches via finite …