Development and Laboratory Testing of a Multipoint Displacement Monitoring System

Darragh Lydon*, Su Taylor, Des Robinson, Necati Catbas, Myra Lydon

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper develops a synchronized multi-camera contactless vision based multiple point displacement measurement system using wireless action cameras. Displacement measurements can provide a valuable insight into the structural condition and service behavior of bridges under live loading. Traditional means of obtaining displacement readings include displacement gauges or GPS based systems which can be limited in terms of accuracy and access. Computer Vision systems can provide a promising alternative means of displacement calculation, however existing systems in use are limited in scope by their inability to reliably track multiple points on a long span bridge structure. The system introduced in this paper provides a low-cost durable alternative which is rapidly deployable. Commercial action cameras were paired with an industrially validated solution for synchronization to provide multiple point displacement readings. The performance of the system was evaluated in a series of controlled laboratory tests. This included the development of displacement identification algorithms which were rigorously tested and validated against fiber optic displacement measurements. The results presented in this paper provide the knowledge for a step change in the application current vision based Structural health monitoring (SHM) systems which can be cost prohibitive and provides rapid method of obtaining data which accurately relates to measured bridge deflections.

Original languageEnglish
Title of host publicationAdvances in Computer Vision: Proceedings of the 2019 Computer Vision Conference CVC
EditorsKohei Arai, Supriya Kapoor
PublisherSpringer Verlag
Pages629-638
Number of pages10
Volume943
ISBN (Print)9783030177942
DOIs
Publication statusPublished - 2020
EventComputer Vision Conference, CVC 2019 - Las Vegas, United States
Duration: 25 Apr 201926 Apr 2019

Publication series

NameAdvances in Intelligent Systems and Computing
Volume943
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

ConferenceComputer Vision Conference, CVC 2019
Country/TerritoryUnited States
CityLas Vegas
Period25/04/201926/04/2019

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

Keywords

  • Bridge monitoring
  • Computer vision
  • Structural health monitoring

ASJC Scopus subject areas

  • Control and Systems Engineering
  • General Computer Science

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