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 …

[HTML][HTML] Review of machine-learning techniques applied to structural health monitoring systems for building and bridge structures

A Gomez-Cabrera, PJ Escamilla-Ambrosio - Applied Sciences, 2022‏ - mdpi.com
This review identifies current machine-learning algorithms implemented in building
structural health monitoring systems and their success in determining the level of damage in …

Semi-supervised multi-sensor information fusion tailored graph embedded low-rank tensor learning machine under extremely low labeled rate

H Xu, X Wang, J Huang, F Zhang, F Chu - Information Fusion, 2024‏ - Elsevier
This paper investigates a demanding and meaningful task of intelligent fault diagnosis, in
which multi-sensors signals are fused for semi-supervised analysis with few labeled fault …

Time-varying damage detection in beam structures using variational mode decomposition and continuous wavelet transform

JL Liu, SF Wang, YZ Li, AH Yu - Construction and Building Materials, 2024‏ - Elsevier
Civil engineering structures in operation are likely to suffer damage. During the service life,
structural damage evolves gradually from minor to severe. However, most current studies …

Damage detection and localization of a steel truss bridge model subjected to impact and white noise excitations using empirical wavelet transform neural network …

AA Mousavi, C Zhang, SF Masri, G Gholipour - Measurement, 2021‏ - Elsevier
This paper aims to present a computational and experimental investigation on the
performance of a new damage detection approach based on empirical wavelet transform …

A global–local meta-modelling technique for model updating

G Dessena, DI Ignatyev, JF Whidborne… - Computer Methods in …, 2024‏ - Elsevier
The finite element model updating procedure of large or complex structures is challenging
for engineering practitioners and researchers. Iterative methods, such as genetic algorithms …

[HTML][HTML] A data-driven methodology for bridge indirect health monitoring using unsupervised computer vision

AC Hurtado, MM Alamdari, E Atroshchenko… - … Systems and Signal …, 2024‏ - Elsevier
In recent years, researchers have extensively explored the application of drive-by inspection
technology for bridge damage assessment. This approach involves using the response of a …

A Loewner‐Based System Identification and Structural Health Monitoring Approach for Mechanical Systems

G Dessena, M Civera… - … Control and Health …, 2023‏ - Wiley Online Library
Data‐driven structural health monitoring (SHM) requires precise estimates of the target
system behaviour. In this sense, SHM by means of modal parameters is strictly linked to …

[HTML][HTML] An efficient automatic modal identification method based on free vibration response and enhanced Empirical Fourier Decomposition technique

M Mazzeo, D De Domenico, G Quaranta… - Engineering Structures, 2024‏ - Elsevier
This paper presents an efficient yet practical approach for the automatic modal identification
of structures based on their free vibration response. The proposed approach relies on the …

A machine learning approach for automatic operational modal analysis

V Mugnaini, LZ Fragonara, M Civera - Mechanical Systems and Signal …, 2022‏ - Elsevier
One of the major applications of Structural Dynamics in Civil, Mechanical, or Aerospace
Engineering regards the dynamic characterisation of man-made structures and components …