Computer vision-based in-situ bridge displacement measurement
The displacement responses of a bridge structure subjected to moving vehicle load can be used to reflect the information of structural stiffness and load-carrying capacity. This study develops a target-free computer vision-based approach as an alternative to conventional displacement sensors for mea...
| Main Authors: | , , , , |
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| Format: | Conference Paper |
| Published: |
2023
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| Online Access: | https://nla.gov.au/nla.obj-3272579398/view http://hdl.handle.net/20.500.11937/97952 |
| _version_ | 1848766343687438336 |
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| author | Peng, Zhen Li, Jun Chen, Wensu Hossain, R. Atkinson, S. |
| author_facet | Peng, Zhen Li, Jun Chen, Wensu Hossain, R. Atkinson, S. |
| author_sort | Peng, Zhen |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The displacement responses of a bridge structure subjected to moving vehicle load can be used to reflect the information of structural stiffness and load-carrying capacity. This study develops a target-free computer vision-based approach as an alternative to conventional displacement sensors for measuring bridge displacement responses in a contactless manner. This approach involves camera calibration and scale factor determination, natural feature target identification and description, feature matching and tracking. The developed approach is applied for the vibration displacement measurement of Stirling Bridge in Fremantle, Western Australia exposed to normal traffic. The Stirling Bridge has been selected due to the significant number of fully loaded trucks that pass through it, traveling from the North Fremantle Port to Perth City. The identification results agree well with the traffic patterns recorded from a traffic camera installed on the bridge deck. The developed technique provides an affordable and easily deployable alternative to conventional contact-type displacement sensor, which can be used for timely bridge health condition assessment. |
| first_indexed | 2025-11-14T11:49:38Z |
| format | Conference Paper |
| id | curtin-20.500.11937-97952 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:49:38Z |
| publishDate | 2023 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-979522025-07-10T08:47:44Z Computer vision-based in-situ bridge displacement measurement Peng, Zhen Li, Jun Chen, Wensu Hossain, R. Atkinson, S. The displacement responses of a bridge structure subjected to moving vehicle load can be used to reflect the information of structural stiffness and load-carrying capacity. This study develops a target-free computer vision-based approach as an alternative to conventional displacement sensors for measuring bridge displacement responses in a contactless manner. This approach involves camera calibration and scale factor determination, natural feature target identification and description, feature matching and tracking. The developed approach is applied for the vibration displacement measurement of Stirling Bridge in Fremantle, Western Australia exposed to normal traffic. The Stirling Bridge has been selected due to the significant number of fully loaded trucks that pass through it, traveling from the North Fremantle Port to Perth City. The identification results agree well with the traffic patterns recorded from a traffic camera installed on the bridge deck. The developed technique provides an affordable and easily deployable alternative to conventional contact-type displacement sensor, which can be used for timely bridge health condition assessment. 2023 Conference Paper http://hdl.handle.net/20.500.11937/97952 https://nla.gov.au/nla.obj-3272579398/view unknown |
| spellingShingle | Peng, Zhen Li, Jun Chen, Wensu Hossain, R. Atkinson, S. Computer vision-based in-situ bridge displacement measurement |
| title | Computer vision-based in-situ bridge displacement measurement |
| title_full | Computer vision-based in-situ bridge displacement measurement |
| title_fullStr | Computer vision-based in-situ bridge displacement measurement |
| title_full_unstemmed | Computer vision-based in-situ bridge displacement measurement |
| title_short | Computer vision-based in-situ bridge displacement measurement |
| title_sort | computer vision-based in-situ bridge displacement measurement |
| url | https://nla.gov.au/nla.obj-3272579398/view http://hdl.handle.net/20.500.11937/97952 |