Characterizing Footbridge Response from Cyclist Crossings with Computer Vision-Based Monitoring

Rolands Kromanis*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Computer vision applications are frequently selected for short-term monitoring of bridges. The availability of high resolution and frame rate consumer-grade cameras such as action cameras makes the computer vision-based monitoring an attractive and affordable option. This paper presents findings from monitoring deformations of a steel girder footbridge subjected to cyclist loads captured with an action camera. A modified GoPro action camera with a zoom lens was located 35 m from the centre of the bridge. High resolution (720 × 1080 pixel) and high frame rate (240 fps) videos were recorded during cyclist crossings. Image processing, measurement denoising, vertical deflection interpretation and influence line (bridge signature) derivations are presented and discussed. Both static and dynamic responses are identifiable (discernible in vision measurements) and even tiny (a fraction of a millimetre) vertical deflections can be accurately computed from videos collected with the action camera.

Original languageEnglish
Title of host publicationCivil Structural Health Monitoring
Subtitle of host publicationProceedings of CSHM-8 Workshop
EditorsCarlo Rainieri, Giovanni Fabbrocino, Nicola Caterino, Francesca Ceroni, Matilde A. Notarangelo
Place of PublicationCham
PublisherSpringer
Pages83-95
Number of pages13
ISBN (Electronic)978-3-030-74258-4
ISBN (Print)978-3-030-74257-7
DOIs
Publication statusE-pub ahead of print/First online - 25 Aug 2021
Event8th Civil Structural Health Monitoring Workshop, CSHM-8 2021 - Virtual, Online
Duration: 31 Mar 20212 Apr 2021

Publication series

NameLecture Notes in Civil Engineering
Volume156
ISSN (Print)2366-2557
ISSN (Electronic)2366-2565

Conference

Conference8th Civil Structural Health Monitoring Workshop, CSHM-8 2021
Period31/03/212/04/21

Keywords

  • Computer vision-based monitoring
  • Deformation monitoring
  • Measurement pre-processing
  • Signal interpretation
  • Structural dynamics
  • Vertical deflections

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