Abstract
During construction and maintenance of concrete structures, it is important to achieve and preserve good surface quality of their components. The current quality assessment for concrete surfaces, however, heavily relies on manual inspection, which is time demanding and costly. This study presents a new technique that can simultaneously localize and quantify spalling defects on concrete surfaces using a terrestrial laser scanner. Defect-sensitive features, which have complementary properties to each other, are developed and combined for improved localization and quantification of spalling defects. A defect classifier is developed to automatically diagnose whether the investigated surface region is damaged, where the defect is located, and how large it is. Numerical simulations and experiments are conducted to demonstrate the effectiveness of the proposed defect-detection technique. Furthermore, a parametric study with varying scan parameters is performed for optimal detection performance. The results demonstrate that the proposed technique can properly estimate the location and volume of the concrete spalling defects.
Original language | English |
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Article number | 04014086 |
Journal | Journal of Computing in Civil Engineering |
Volume | 29 |
Issue number | 6 |
DOIs | |
Publication status | Published - 1 Jan 2015 |
Externally published | Yes |
Keywords
- Concrete surface
- Defect localization and defect quantification
- Quality assessment
- Spalling defect
- Terrestrial laser scanner
ASJC Scopus subject areas
- Civil and Structural Engineering
- Computer Science Applications