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Smart Structures and Systems Volume 25, Number 6, June 2020 , pages 733-749 DOI: https://doi.org/10.12989/sss.2020.25.6.733 |
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Autonomous vision-based damage chronology for spatiotemporal condition assessment of civil infrastructure using unmanned aerial vehicle |
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Tarutal Ghosh Mondal and Mohammad R. Jahanshahi
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| Abstract | ||
| This study presents a computer vision-based approach for representing time evolution of structural damages leveraging a database of inspection images. Spatially incoherent but temporally sorted archival images captured by robotic cameras are exploited to represent the damage evolution over a long period of time. An access to a sequence of time-stamped inspection data recording the damage growth dynamics is premised to this end. Identification of a structural defect in the most recent inspection data set triggers an exhaustive search into the images collected during the previous inspections looking for correspondences based on spatial proximity. This is followed by a view synthesis from multiple candidate images resulting in a single reconstruction for each inspection round. Cracks on concrete surface are used as a case study to demonstrate the feasibility of this approach. Once the chronology is established, the damage severity is quantified at various levels of time scale documenting its progression through time. The proposed scheme enables the prediction of damage severity at a future point in time providing a scope for preemptive measures against imminent structural failure. On the whole, it is believed that the present study will immensely benefit the structural inspectors by introducing the time dimension into the autonomous condition assessment pipeline. | ||
| Key Words | ||
| damage chronology; vision-based inspection; autonomous condition assessment; UAV; civil infrastructures | ||
| Address | ||
| (1) Tarutal Ghosh Mondal, Mohammad R. Jahanshahi: Lyles School of Civil Engineering, Purdue University, West Lafayette, IN, USA; (2) Mohammad R. Jahanshahi: School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA. | ||