Three decades of statistical pattern recognition paradigm for SHM of bridges

E Figueiredo, J Brownjohn - Structural Health Monitoring, 2022 - journals.sagepub.com
Bridges play a crucial role in modern societies, regardless of their culture, geographical
location, or economic development. The safest, economical, and most resilient bridges are …

Vibration-based damage detection techniques used for health monitoring of structures: a review

S Das, P Saha, SK Patro - Journal of Civil Structural Health Monitoring, 2016 - Springer
Structural health monitoring (SHM) techniques have been studied for several years. An
effective approach for SHM is to choose the parameters that are sensitive to the damage …

Data-driven support vector machine with optimization techniques for structural health monitoring and damage detection

G Gui, H Pan, Z Lin, Y Li, Z Yuan - KSCE Journal of Civil Engineering, 2017 - Springer
Rapid detecting damages/defeats in the large-scale civil engineering structures, assessing
their conditions and timely decision making are crucial to ensure their health and ultimately …

Data-driven structural health monitoring using feature fusion and hybrid deep learning

HV Dang, H Tran-Ngoc, TV Nguyen… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Smart structural health monitoring (SHM) for large-scale infrastructure is an intriguing
subject for engineering communities thanks to its significant advantages such as timely …

Unsupervised learning methods for data-driven vibration-based structural health monitoring: a review

K Eltouny, M Gomaa, X Liang - Sensors, 2023 - mdpi.com
Structural damage detection using unsupervised learning methods has been a trending
topic in the structural health monitoring (SHM) research community during the past decades …

Machine learning algorithms for damage detection under operational and environmental variability

E Figueiredo, G Park, CR Farrar… - Structural Health …, 2011 - journals.sagepub.com
The goal of this article is to detect structural damage in the presence of operational and
environmental variations using vibration-based damage identification procedures. For this …

A comparative analysis of signal decomposition techniques for structural health monitoring on an experimental benchmark

M Civera, C Surace - Sensors, 2021 - mdpi.com
Signal Processing is, arguably, the fundamental enabling technology for vibration-based
Structural Health Monitoring (SHM), which includes damage detection and more advanced …

Machine learning algorithms for damage detection: Kernel-based approaches

A Santos, E Figueiredo, MFM Silva, CS Sales… - Journal of Sound and …, 2016 - Elsevier
This paper presents four kernel-based algorithms for damage detection under varying
operational and environmental conditions, namely based on one-class support vector …

Sensor data-driven structural damage detection based on deep convolutional neural networks and continuous wavelet transform

Z Chen, Y Wang, J Wu, C Deng, K Hu - Applied Intelligence, 2021 - Springer
Structural damage detection is of very importance to improve reliability and safety of civil
structures. A novel sensor data-driven structural damage detection method is proposed in …

An unsupervised learning approach by novel damage indices in structural health monitoring for damage localization and quantification

A Entezami, H Shariatmadar - Structural Health Monitoring, 2018 - journals.sagepub.com
The aim of this article is to propose novel damage indices for damage localization and
quantification based on time series modeling. In order to extract damage-sensitive features …