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 language | English |
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Title of host publication | Advances in Computer Vision: Proceedings of the 2019 Computer Vision Conference CVC |
Editors | Kohei Arai, Supriya Kapoor |
Publisher | Springer Verlag |
Pages | 629-638 |
Number of pages | 10 |
Volume | 943 |
ISBN (Print) | 9783030177942 |
DOIs | |
Publication status | Published - 2020 |
Event | Computer Vision Conference, CVC 2019 - Las Vegas, United States Duration: 25 Apr 2019 → 26 Apr 2019 |
Publication series
Name | Advances in Intelligent Systems and Computing |
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Volume | 943 |
ISSN (Print) | 2194-5357 |
ISSN (Electronic) | 2194-5365 |
Conference
Conference | Computer Vision Conference, CVC 2019 |
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Country/Territory | United States |
City | Las Vegas |
Period | 25/04/2019 → 26/04/2019 |
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