Unsupervised Machine Learning for Robust Bridge Damage Detection: Full-Scale Experimental Validation

•An unsupervised Machine Learning scheme is developed for bridge damage detection•Validation is carried out using full scale experiments, a crash test for inducing realistic damages•The method does not require measuring vehicle weights and speeds•It is robust to sensor noise & works sparse senso...

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Bibliographic Details

Published in:	Engineering structures Vol. 249; p. 113250
Main Authors:	Akintunde, Emmanuel, Eftekhar Azam, Saeed, Rageh, Ahmed, Linzell, Daniel G.
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier Ltd 15-12-2021 Elsevier BV
Subjects:	Bridge decks Damage assessment Damage detection Field tests Herbivores Independent component analysis Learning algorithms Live loads Machine learning Mockups Robustness Singular value decomposition Structural response Unsupervised learning
Online Access:	Get full text
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