Vibration feature extraction using signal processing techniques for structural health monitoring: A review

C Zhang, AA Mousavi, SF Masri, G Gholipour… - … Systems and Signal …, 2022 - Elsevier
Structural health monitoring (SHM) has become an important and hot topic for decades in
various fields of civil, mechanical, automotive, and aerospace engineering, etc. Estimating …

Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights

A Malekloo, E Ozer, M AlHamaydeh… - Structural Health …, 2022 - journals.sagepub.com
Conventional damage detection techniques are gradually being replaced by state-of-the-art
smart monitoring and decision-making solutions. Near real-time and online damage …

Data-driven structural health monitoring and damage detection through deep learning: State-of-the-art review

M Azimi, AD Eslamlou, G Pekcan - Sensors, 2020 - mdpi.com
Data-driven methods in structural health monitoring (SHM) is gaining popularity due to
recent technological advancements in sensors, as well as high-speed internet and cloud …

[HTML][HTML] Intelligent damage diagnosis in bridges using vibration-based monitoring approaches and machine learning: a systematic review

R Niyirora, W Ji, E Masengesho, J Munyaneza… - Results in …, 2022 - Elsevier
Damage detection and safety assessment play a prominent role in the integrity management
of bridge structures. Environmental and operational variability are the leading factors that …

Machine learning applied to the design and inspection of reinforced concrete bridges: Resilient methods and emerging applications

W Fan, Y Chen, J Li, Y Sun, J Feng, H Hassanin… - Structures, 2021 - Elsevier
Abstract Machine learning is one of the key pillars of industry 4.0 that has enabled rapid
technological advancement through establishing complex connections among …

Deep learning for optical sensor applications: A review

NH Al-Ashwal, KAM Al Soufy, ME Hamza, MA Swillam - Sensors, 2023 - mdpi.com
Over the past decade, deep learning (DL) has been applied in a large number of optical
sensors applications. DL algorithms can improve the accuracy and reduce the noise level in …

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 …

Towards smart cities: crowdsensing-based monitoring of transportation infrastructure using in-traffic vehicles

Q Mei, M Gül, N Shirzad-Ghaleroudkhani - Journal of Civil Structural …, 2020 - Springer
This paper presents a novel framework for transportation infrastructure monitoring using
sensors in crowdsourced moving vehicles. Vehicles equipped with various kinds of sensors …

A deep feed-forward neural network for damage detection in functionally graded carbon nanotube-reinforced composite plates using modal kinetic energy

HQ Le, TT Truong, D Dinh-Cong… - Frontiers of Structural and …, 2021 - Springer
This paper proposes a new Deep Feed-forward Neural Network (DFNN) approach for
damage detection in functionally graded carbon nanotube-reinforced composite (FG …

A review of latest trends in bridge health monitoring

N Catbas, O Avci - Proceedings of the Institution of Civil …, 2022 - icevirtuallibrary.com
Structural damage is inherent in civil engineering structures, and bridges are no exception. It
is vital to monitor and keep track of damage in bridge structures as a result of multiple …