: The monitoring of the structural health of infrastructures is a very important topic in structural engineering, but unfortunately, there are few established techniques that are applicable in a wide range of situations. In this paper, we present a new method that adapts image analysis tools and methodologies, taken from the field of computer vision, and applies them to the monitoring signals of a railway bridge. We show that our method correctly identifies changes in the structural health of the bridge with very high precision, thus providing a better, simpler, and more general alternative to current methodologies used in the field.
Dettaglio pubblicazione
2023, SCIENTIFIC REPORTS, Pages 3916- (volume: 13)
Anomaly detection in railway bridges using imaging techniques (01a Articolo in rivista)
Russo Paolo, Schaerf Marco
Gruppo di ricerca: Computer Vision, Computer Graphics, Deep Learning
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