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
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.
引用
收藏
页数:21
相关论文
共 51 条
  • [11] Modal properties identification of a novel sandwich footbridge - Comparison of measured dynamic response and FEA
    Chroscielewski, Jacek
    Miskiewicz, Mikolaj
    Pyrzowski, Lukasz
    Rucka, Magdalena
    Sobczyk, Bartosz
    Wilde, Krzysztof
    [J]. COMPOSITES PART B-ENGINEERING, 2018, 151 : 245 - 255
  • [12] Darby P., BRIDGE INSPECTING UN
  • [13] Segmentation algorithms for thermal images
    Duarte, A.
    Carrao, L.
    Espanha, M.
    Viana, T.
    Freitas, D.
    Bartolo, P.
    Faria, P.
    Almeida, H. A.
    [J]. CENTERIS 2014 - CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS / PROJMAN 2014 - INTERNATIONAL CONFERENCE ON PROJECT MANAGEMENT / HCIST 2014 - INTERNATIONAL CONFERENCE ON HEALTH AND SOCIAL CARE INFORMATION SYSTEMS AND TECHNOLOGIES, 2014, 16 : 1560 - 1569
  • [14] FANG Y, 2019, SUSTAINABILITY-BASEL, V11, DOI DOI 10.3390/SU11195524
  • [15] Experimental validation of cost-effective vision-based structural health monitoring
    Feng, Dongming
    Feng, Maria Q.
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2017, 88 : 199 - 211
  • [16] A Vision-Based Sensor for Noncontact Structural Displacement Measurement
    Feng, Dongming
    Feng, Maria Q.
    Ozer, Ekin
    Fukuda, Yoshio
    [J]. SENSORS, 2015, 15 (07): : 16557 - 16575
  • [17] An innovative image-processing model for rust detection using Perlin Noise to simulate oxide textures
    Gamarra Acosta, Margarita R.
    Velez Diaz, Juan C.
    Schettini Castro, Norelli
    [J]. CORROSION SCIENCE, 2014, 88 : 141 - 151
  • [18] Gardner L, 2017, The Behaviour and Design of Steel Structures to EC3
  • [19] Payload for Contact Inspection Tasks with UAV Systems
    Gonzalez-deSantos, L. M.
    Martinez-Sanchez, J.
    Gonzalez-Jorge, H.
    Ribeiro, M.
    de Sousa, J. B.
    Arias, P.
    [J]. SENSORS, 2019, 19 (17)
  • [20] Unmanned Aerial Systems for Civil Applications: A Review
    Gonzalez-Jorge, Higinio
    Martinez-Sanchez, Joaquin
    Bueno, Martin
    Arias, Pedor
    [J]. DRONES, 2017, 1 (01) : 1 - 19