共 51 条
Framework for Structural Health Monitoring of Steel Bridges by Computer Vision
被引:30
作者:
Marchewka, Adam
[1
]
Ziolkowski, Patryk
[2
]
Aguilar-Vidal, Victor
[3
,4
]
机构:
[1] Univ Sci & Technol Bydgoszcz, Fac Telecommun, Comp Sci & Elect Engn, Al Prof S Kaliskiego 7, PL-85796 Bydgoszcz, Poland
[2] Gdansk Univ Technol, Fac Civil & Environm Engn, Gabriela Narutowicza 11-12, PL-80233 Gdansk, Poland
[3] Auburn Univ, Dept Civil Engn, 261 W Magnolia Ave, Auburn, AL 36849 USA
[4] Univ San Sebastian, Fac Ingn & Tecnol, Lientur 1457, Concepcion 4080871, Chile
来源:
关键词:
computer vision;
drones;
image processing;
steel structures;
structural health monitoring;
IMAGES;
SEGMENTATION;
RELIABILITY;
D O I:
10.3390/s20030700
中图分类号:
O65 [分析化学];
学科分类号:
070302 ;
081704 ;
摘要:
The monitoring of a structural condition of steel bridges is an important issue. Good condition of infrastructure facilities ensures the safety and economic well-being of society. At the same time, due to the continuous development, rising wealth of the society and socio-economic integration of countries, the number of infrastructural objects is growing. Therefore, there is a need to introduce an easy-to-use and relatively low-cost method of bridge diagnostics. We can achieve these benefits by the use of Unmanned Aerial Vehicle-Based Remote Sensing and Digital Image Processing. In our study, we present a state-of-the-art framework for Structural Health Monitoring of steel bridges that involves literature review on steel bridges health monitoring, drone route planning, image acquisition, identification of visual markers that may indicate a poor condition of the structure and determining the scope of applicability. The presented framework of image processing procedure is suitable for diagnostics of steel truss riveted bridges. In our considerations, we used photographic documentation of the Fitzpatrick Bridge located in Tallassee, Alabama, USA.
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页数:21
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