Automated defect detection in FRP-bonded structures by Eulerian video magnification and adaptive background mixture model

被引:11
作者
Qiu, Qiwen [1 ]
机构
[1] Hong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong, Peoples R China
关键词
Defect detection; Civil engineering structure; Fiber-reinforced polymer; Computer-aided engineering; Automation; Motion magnification; High-speed video; Computer vision; Information technology; Non-destructive testing; RADAR NDT TECHNIQUE; ACOUSTIC-LASER; INFRARED THERMOGRAPHY; DAMAGE DETECTION; CONCRETE BEAMS; DURABILITY; VISION; REHABILITATION; PARAMETERS; SYSTEM;
D O I
10.1016/j.autcon.2020.103244
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
A computer-aided methodology for automated defect detection in fiber-reinforced polymer (FRP) bonded civil engineering structures via Eulerian video magnification integrated with adaptive background mixture model is demonstrated. In this methodology, Eulerian video magnification is firstly used to render the stimulated debonding motion visible in a high-speed and high-resolution video. Then, adaptive background mixture model is applied in the motion-magnified video for automated tracking of the de-bonding motion. The combined use of these two computer-aided vision techniques aims at developing an innovative way for intuitive, straightforward, and automated defect detection. In the application of this methodology, two operational parameters (i.e. motion amplification factor and de-noising factor) in the video processing can greatly affect the sensitivity of defect detection. After evaluation of their effects, the present work shows a practice guide for adjusting the above two influencing parameters in order to improve the automated defect detection.
引用
收藏
页数:12
相关论文
共 63 条
[1]   An intelligent adjustable spanner for automated engagement with multi-diameter bolts/nuts during tightening/loosening process using vision system and fuzzy logic [J].
Ali, Mohammed A. H. ;
Alshameri, Mohammed A. .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2019, 101 (9-12) :2795-2813
[2]  
Ngo ACL, 2016, INT CONF ACOUST SPEE, P1243, DOI 10.1109/ICASSP.2016.7471875
[3]  
[Anonymous], 2005, INT C IND TECHN ICIT
[4]  
[Anonymous], 2013, COD PRACT STRUCT US
[5]  
[Anonymous], 2000, 4562000 IS
[6]   Far-field radar NDT technique for detecting GFRP debonding from concrete [J].
Bueyuekoeztuerk, Oral ;
Yu, Tzu-Yang .
CONSTRUCTION AND BUILDING MATERIALS, 2009, 23 (04) :1678-1689
[7]   Durability of FRP - concrete bonded joints in structural rehabilitation: A review [J].
Cabral-Fonseca, S. ;
Correia, J. R. ;
Custodio, J. ;
Silva, H. M. ;
Machado, A. M. ;
Sousa, J. .
INTERNATIONAL JOURNAL OF ADHESION AND ADHESIVES, 2018, 83 :153-167
[8]   Operational and defect parameters concerning the acoustic-laser vibrometry method for FRP-reinforced concrete [J].
Chen, Justin G. ;
Haupt, Robert W. ;
Buyukozturk, Oral .
NDT & E INTERNATIONAL, 2015, 71 :43-53
[9]   A self-adaptive Gaussian mixture model [J].
Chen, Zezhi ;
Ellis, Tim .
COMPUTER VISION AND IMAGE UNDERSTANDING, 2014, 122 :35-46
[10]   Vibrational characteristics of FRP-bonded concrete interfacial defects in a low frequency regime [J].
Cheng, Tin Kei ;
Lau, Denvid .
NONDESTRUCTIVE CHARACTERIZATION FOR COMPOSITE MATERIALS, AEROSPACE ENGINEERING, CIVIL INFRASTRUCTURE, AND HOMELAND SECURITY 2014, 2014, 9063