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[HTML][HTML] Abnormal data detection for structural health monitoring: State-of-the-art review
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 …
performance of engineering structures such as, buildings, bridges, dams, and tunnels …
A literature review: Generative adversarial networks for civil structural health monitoring
Structural Health Monitoring (SHM) of civil structures has been constantly evolving with
novel methods, advancements in data science, and more accessible technology to address …
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
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 …
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
In structural health monitoring (SHM) systems, data loss inevitably occurs and reduces the
applicability of SHM techniques, such as condition assessment and damage identification …
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
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 …
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
This paper presents a footbridge damage detection and classification framework using
smartphone-recorded responses of micromobility and deep learning techniques. Time …
smartphone-recorded responses of micromobility and deep learning techniques. Time …
A multi-task learning-based automatic blind identification procedure for operational modal analysis
Traditional modal analysis approaches for structural heath monitoring (SHM) have a low
implementation efficiency. This study develops an artificial intelligence (AI)-based automatic …
implementation efficiency. This study develops an artificial intelligence (AI)-based automatic …
The application of deep learning in bridge health monitoring: A literature review
Along with the advancement in sensing and communication technologies, the explosion in
the measurement data collected by structural health monitoring (SHM) systems installed 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
The dimensional quality of precast concrete (PC) subcomponents (concrete and rebars)
should be inspected in advance to ensure assembly quality. Currently, PC components are …
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
Structural damage identification approaches can be divided into two categories, ie data-
driven approaches via statistical pattern recognition and model-based approaches via finite …
driven approaches via statistical pattern recognition and model-based approaches via finite …