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

Rolands Kromanis

doi:10.1007/978-3-030-74258-4_5

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

Rolands Kromanis^*

^*Corresponding author for this work

Construction Management and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

1 Citation (Scopus)

17 Downloads (Pure)

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 language	English
Title of host publication	Civil Structural Health Monitoring
Subtitle of host publication	Proceedings of CSHM-8 Workshop
Editors	Carlo Rainieri, Giovanni Fabbrocino, Nicola Caterino, Francesca Ceroni, Matilde A. Notarangelo
Place of Publication	Cham
Publisher	Springer
Pages	83-95
Number of pages	13
ISBN (Electronic)	978-3-030-74258-4
ISBN (Print)	978-3-030-74257-7
DOIs	https://doi.org/10.1007/978-3-030-74258-4_5
Publication status	Published - 25 Aug 2021
Event	8th Civil Structural Health Monitoring Workshop, CSHM-8 2021 - Virtual, Online Duration: 31 Mar 2021 → 2 Apr 2021

Publication series

Name	Lecture Notes in Civil Engineering
Volume	156
ISSN (Print)	2366-2557
ISSN (Electronic)	2366-2565

Conference

Conference	8th Civil Structural Health Monitoring Workshop, CSHM-8 2021
Period	31/03/21 → 2/04/21

Keywords

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

Access to Document

10.1007/978-3-030-74258-4_5

Kromanis2021_Chapter_CharacterizingFootbridgeResponFinal published version, 657 KBLicence: Taverne

Cite this

Kromanis, R. (2021). Characterizing Footbridge Response from Cyclist Crossings with Computer Vision-Based Monitoring. In C. Rainieri, G. Fabbrocino, N. Caterino, F. Ceroni, & M. A. Notarangelo (Eds.), Civil Structural Health Monitoring: Proceedings of CSHM-8 Workshop (pp. 83-95). (Lecture Notes in Civil Engineering; Vol. 156). Springer. https://doi.org/10.1007/978-3-030-74258-4_5

@inproceedings{dd623296432d4528bb2aa90d36aafe84,

title = "Characterizing Footbridge Response from Cyclist Crossings with Computer Vision-Based Monitoring",

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.",

keywords = "Computer vision-based monitoring, Deformation monitoring, Measurement pre-processing, Signal interpretation, Structural dynamics, Vertical deflections",

author = "Rolands Kromanis",

note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 8th Civil Structural Health Monitoring Workshop, CSHM-8 2021 ; Conference date: 31-03-2021 Through 02-04-2021",

year = "2021",

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doi = "10.1007/978-3-030-74258-4_5",

language = "English",

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series = "Lecture Notes in Civil Engineering",

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Kromanis, R 2021, Characterizing Footbridge Response from Cyclist Crossings with Computer Vision-Based Monitoring. in C Rainieri, G Fabbrocino, N Caterino, F Ceroni & MA Notarangelo (eds), Civil Structural Health Monitoring: Proceedings of CSHM-8 Workshop. Lecture Notes in Civil Engineering, vol. 156, Springer, Cham, pp. 83-95, 8th Civil Structural Health Monitoring Workshop, CSHM-8 2021, 31/03/21. https://doi.org/10.1007/978-3-030-74258-4_5

Characterizing Footbridge Response from Cyclist Crossings with Computer Vision-Based Monitoring. / Kromanis, Rolands.

Civil Structural Health Monitoring: Proceedings of CSHM-8 Workshop. ed. / Carlo Rainieri; Giovanni Fabbrocino; Nicola Caterino; Francesca Ceroni; Matilde A. Notarangelo. Cham : Springer, 2021. p. 83-95 (Lecture Notes in Civil Engineering; Vol. 156).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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N2 - 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.

AB - 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.

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ER -

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

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