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Bridge deck delamination identification from unmanned aerial vehicle infrared imagery
Abstract The rapid, cost-effective, and non-disruptive assessment of bridge deck condition has emerged as a critical challenge for bridge maintenance. Deck delaminations are a common form of deterioration which has been assessed, historically, through chain-drag techniques and more recently through nondestructive evaluation (NDE) including both acoustic and optical methods. Although NDE methods have proven to be capable to provide information related to the existence of delaminations in bridge decks, many of them are time-consuming, labor-intensive, expensive, while they further require significant disruptions to traffic. In this context, this article demonstrates the capability of unmanned aerial vehicles (UAVs) equipped with both color and infrared cameras to rapidly and effectively detect and estimate the size of regions where subsurface delaminations exist. To achieve this goal, a novel image post-processing algorithm was developed to use such multispectral imagery obtained by a UAV. To evaluate the capabilities of the presented approach, a bridge deck mockup with pre-manufactured defects was tested. The major advantages of the presented approach include its capability to rapidly identify locations where delaminations exist, as well as its potential to automate bridge-deck related damage detection procedures and further guide investigations using other higher accuracy and ground-based approaches.
Highlights Multispectral imagery of a concrete bridge deck is collected using a UAV. Aerial infrared images reveal delaminations in the concrete deck. An algorithm is developed for automated detection and sizing of delaminations. The UAV data and its processing could support rapid assessment of infrastructures.
Bridge deck delamination identification from unmanned aerial vehicle infrared imagery
Abstract The rapid, cost-effective, and non-disruptive assessment of bridge deck condition has emerged as a critical challenge for bridge maintenance. Deck delaminations are a common form of deterioration which has been assessed, historically, through chain-drag techniques and more recently through nondestructive evaluation (NDE) including both acoustic and optical methods. Although NDE methods have proven to be capable to provide information related to the existence of delaminations in bridge decks, many of them are time-consuming, labor-intensive, expensive, while they further require significant disruptions to traffic. In this context, this article demonstrates the capability of unmanned aerial vehicles (UAVs) equipped with both color and infrared cameras to rapidly and effectively detect and estimate the size of regions where subsurface delaminations exist. To achieve this goal, a novel image post-processing algorithm was developed to use such multispectral imagery obtained by a UAV. To evaluate the capabilities of the presented approach, a bridge deck mockup with pre-manufactured defects was tested. The major advantages of the presented approach include its capability to rapidly identify locations where delaminations exist, as well as its potential to automate bridge-deck related damage detection procedures and further guide investigations using other higher accuracy and ground-based approaches.
Highlights Multispectral imagery of a concrete bridge deck is collected using a UAV. Aerial infrared images reveal delaminations in the concrete deck. An algorithm is developed for automated detection and sizing of delaminations. The UAV data and its processing could support rapid assessment of infrastructures.
Bridge deck delamination identification from unmanned aerial vehicle infrared imagery
Ellenberg, A. (author) / Kontsos, A. (author) / Moon, F. (author) / Bartoli, I. (author)
Automation in Construction ; 72 ; 155-165
2016-08-15
11 pages
Article (Journal)
Electronic Resource
English
Bridge deck delamination identification from unmanned aerial vehicle infrared imagery
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