Anomaly detection in railway bridges using imaging techniques

Paolo Russo; Marco Schaerf

doi:10.1038/s41598-023-30683-z

Anomaly detection in railway bridges using imaging techniques

Sci Rep. 2023 Mar 8;13(1):3916. doi: 10.1038/s41598-023-30683-z.

Authors

Paolo Russo¹, Marco Schaerf²

Affiliations

¹ Department of Computer, Control, and Management Engineering "Antonio Ruberti", Sapienza University of Rome, Via Ariosto 25, 00185, Rome, Italy. paolo.russo@uniroma1.it.
² Department of Computer, Control, and Management Engineering "Antonio Ruberti", Sapienza University of Rome, Via Ariosto 25, 00185, Rome, Italy.

Abstract

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.