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This paper will demonstrate a solution for detecting damage to a bridge structure from measured displacements gathered using a roving vision sensor based approach. The measurement of displacement was accomplished using a synchronised 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 behaviour of bridges under live loading. Computer Vision systems have been validated as a means of displacement calculation, the research developed here is intended to form the basis of a real time damage detection system. This is done through the use of unsupervised deep learning methods for anomaly detection which could form the basis of a low cost durable alternative which is rapidly deployable in the field. The performance of the system was evaluated in a series of controlled laboratory tests. This research provides a means of detecting changes to a bridge structure through use of minimal sensor installation, reducing potential sources of error and allowing for potential live rating of bridge structures.
|Title of host publication||Civil Structural Health Monitoring Proceedings of CSHM-8 Workshop|
|Publication status||Published - 25 Aug 2021|
|Event||CSHM-8 Civil Structural Health Monitoring Workshop - Pacanowski Palace, Naples, Italy|
Duration: 16 Sep 2020 → 18 Sep 2020
|Conference||CSHM-8 Civil Structural Health Monitoring Workshop|
|Period||16/09/2020 → 18/09/2020|