Concrete Surface Damage Volume Measurement Based on Three-Dimensional Reconstruction by Smartphones

被引:15
作者
Liu, Chengcheng [1 ]
Zhou, Lei [2 ]
Wang, Weiwei [2 ]
Zhao, Xuefeng [1 ]
机构
[1] Dalian Univ Technol, State Key Lab Coastal & Offshore Engn, Fac Infrastruct Engn, Dalian 116024, Peoples R China
[2] Offshore Oil Engn Co Ltd, Tianjin 300451, Peoples R China
关键词
Image reconstruction; Three-dimensional displays; Cameras; Surface reconstruction; Phase change materials; Volume measurement; Sensors; Damage volume; depth camera sensor; multi-view stereo reconstruction; point cloud; smartphone; three-dimensional reconstruction; 3D RECONSTRUCTION; PHOTOGRAMMETRY;
D O I
10.1109/JSEN.2021.3067739
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Surface damage of structures is an important indicator that further inspection of the structure is needed. However, existing detection methods rarely detect three-dimensional data of damage. Aiming at the inspection of structural surface damage, this study proposes a method based on 3-D structural surface damage reconstruction techniques for reconstructing and extracting data for damage volume calculation. The surface damage of concrete specimen is three-dimensionally reconstructed using multi-view smartphone-taken images and compared with a depth camera. The point cloud data was obtained, and then the damage plane was fitted and removed by a Random Sample Consensus algorithm to obtain the damage site data, finally, the damage volume was calculated. In the experimental process, accuracy and post-processing difficulty, equipment cost, data acquisition efficiency, and overall applicability of the two methods were compared and analyzed. In conclusion, it was determined that the 3-D damage parameters obtained through the smartphone multi-view stereo reconstruction performs better, at a lower cost and is more convenient for use in inspection work. Finally, the practicability of the method was proved by the damage detection experiment of real building.
引用
收藏
页码:11349 / 11360
页数:12
相关论文
共 34 条
[1]  
Akuta T., 1991, Measurement, V9, P98, DOI 10.1016/0263-2241(91)90028-O
[2]   A Novel Method for 3D Reconstruction of Coronary Bifurcation Using Quantitative Coronary Angiography [J].
Andrikos, Ioannis O. ;
Sakellarios, Atnonis I. ;
Siogkas, Panagiotis K. ;
Tsompou, Panagiota I. ;
Kigka, Vassiliki I. ;
Michalis, Lampros K. ;
Fotiadis, Dimitrios I. .
WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING 2018, VOL 1, 2019, 68 (01) :191-195
[3]  
Arango C., 2015, INT ARCH PHOTOGRAMME, VXL-1/W4, P131, DOI DOI 10.5194/ISPRSARCHIVES-XL-1-W4-131-2015
[4]  
Arens M., 2014, P SPIE EL REM SENS P
[5]  
Babic Steven, 2002, J Appl Clin Med Phys, V3, P170, DOI 10.1120/1.1471552
[6]   Deep learning-based automatic volumetric damage quantification using depth camera [J].
Beckman, Gustavo H. ;
Polyzois, Dimos ;
Cha, Young-Jin .
AUTOMATION IN CONSTRUCTION, 2019, 99 :114-124
[7]   Ground-based and UAV-Based photogrammetry: A multi-scale, high-resolution mapping tool for structural geology and paleoseismology [J].
Bemis, Sean P. ;
Micklethwaite, Steven ;
Turner, Darren ;
James, Mike R. ;
Akciz, Sinan ;
Thiele, Sam T. ;
Bangash, Hasnain Ali .
JOURNAL OF STRUCTURAL GEOLOGY, 2014, 69 :163-178
[8]  
Cao T., 2013, STOMATOLOGY, V33, P165
[9]  
Davis Kathryn E, 2013, J Diabetes Sci Technol, V7, P1161
[10]   Laser-based surface damage detection and quantification using predicted surface properties [J].
Erkal, Burcu Guldur ;
Hajjar, Jerome F. .
AUTOMATION IN CONSTRUCTION, 2017, 83 :285-302