Bridge Pillar Defect Detection using Close Range Thermography Imagery

被引:0
作者
Rasib, Abd Wahid [1 ]
Yaacob, Muhammad Latifi Mohd [1 ]
Idris, Nurul Hawani [1 ]
Zainuddin, Khairulazhar [2 ]
Dollah, Rozilawati [3 ]
Yusof, Norbazlan Mohd [4 ]
Abd Rahaman, Norisam [4 ]
Ahmad, Shahrin [5 ]
Hamid, Norhadi A. [5 ]
Mhapo, Abdul Manaf [5 ]
机构
[1] Univ Teknol Malaysia, Fac Built Environm & Survey, Programme Geoinformat, Johor Baharu, Malaysia
[2] Univ Teknol MARA, Ctr Studies Surveying Sci & Geomat, Perlis, Malaysia
[3] Univ Teknol Malaysia, Fac Engn, Sch Comp, Johor Baharu, Malaysia
[4] PLUS Berhad, Ctr Excellence, Petaling Jaya, Selangor, Malaysia
[5] Geolatitude Technol Sdn Bhd, Johor Baharu, Malaysia
关键词
Defect; detection; bridge pillar; drone; thermography; close range remote sensing;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Currently radiometric thermography image has been explored adequately as alternative advance Non-Destructive Testing (NDT) especially for early detection analysis in various resolution and high degree order image processing, thermography imagery potential to be used in concrete structure defect detection. Therefore, this study is carried out to examine the defect on bridge pillar surface concrete using drone-based thermography sensor (7-13 mu m). Close range remote sensing NDT based on drone platform and imagery segmentation analysis have been applied to interpret the crack line on two Highway. As a result, thermography imagery segmentation and support by multispectral radiometric imagery (RGB) successfully to delineate the micro crack line on the bridge pillar concrete using K-means clustering method. Overall, this study successfully shows the higher order optional platform using drone and thermography sensor that potentially to be applied in forensic concrete structure defect detection for tall structure building.
引用
收藏
页码:599 / 606
页数:8
相关论文
共 16 条
  • [1] Use of the digital image correlation and acoustic emission technique to study the effect of structural size on cracking of reinforced concrete
    Alam, S. Y.
    Loukili, A.
    Grondin, F.
    Roziere, E.
    [J]. ENGINEERING FRACTURE MECHANICS, 2015, 143 : 17 - 31
  • [2] LiDAR based Edge-Detection for Bridge Defect Identification
    Bian, Haitao
    Bai, Libin
    Chen, Shen-En
    Wang, Sheng-Guo
    [J]. NONDESTRUCTIVE CHARACTERIZATION FOR COMPOSITE MATERIALS, AEROSPACE ENGINEERING, CIVIL INFRASTRUCTURE, AND HOMELAND SECURITY 2012, 2012, 8347
  • [3] Cannas B., 2012, P 2012 COMSOL C MIL
  • [4] Dass R., 2012, IMAGE SEGMENTATION T
  • [5] Close-range photogrammetry applications in bridge measurement: Literature review
    Jiang, Ruinian
    Jauregui, David V.
    White, Kenneth R.
    [J]. MEASUREMENT, 2008, 41 (08) : 823 - 834
  • [6] Maldague XPV, 2001, WILEY MICRO, pXV
  • [7] Crack detection using image processing: A critical review and analysis
    Mohan, Arun
    Poobal, Sumathi
    [J]. ALEXANDRIA ENGINEERING JOURNAL, 2018, 57 (02) : 787 - 798
  • [8] Prakash A., 2000, INT ARCH PHOTOGRAMME, VXXXIII
  • [9] Salman M, 2013, IEEE INT C INTELL TR, P2039, DOI 10.1109/ITSC.2013.6728529
  • [10] Log Transform Based Optimal Image Enhancement Using Firefly Algorithm for Autonomous Mini Unmanned Aerial Vehicle: An Application of Aerial Photography
    Samanta, Sourav
    Mukherjee, Amartya
    Ashour, Amira S.
    Dey, Nilanjan
    Tavares, Joao Manuel R. S.
    Karaa, Wahiba Ben Abdessalem
    Taiar, Redha
    Azar, Ahmad Taher
    Hassanien, Aboul Ella
    [J]. INTERNATIONAL JOURNAL OF IMAGE AND GRAPHICS, 2018, 18 (04)