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Dimensional inspection and evaluation method of highway prefabricated components based on 3D model reconstruction technology(PDF)


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Dimensional inspection and evaluation method of highway prefabricated components based on 3D model reconstruction technology
SHI Xue-fei1 XU Zi-qi1 ZHU Rong2 FU Qing-song1
(1. College of Civil Engineering, Tongji University, Shanghai 200092, China; 2. Shanghai Tongji Testing Technology Co., Ltd., Shanghai 200092, China)
bridge engineering special-shaped concrete prefabricated component dimensional inspection and evaluation 3D model reconstruction point cloud denoising point cloud registration
To adapt the manufacturing dimensional inspection and evaluation of special-shaped concrete prefabricated components of highway engineering to the requirements of industrialized construction, the 3D model reconstruction technology was used to inspect and evaluate the dimensions of special-shaped concrete prefabricated components. A high-precision and automated method of the dimensional inspection and evaluationon special-shaped concrete prefabricated components was proposed, including three steps as 3D model reconstruction, point cloud data processing, and inspection and evaluation system. Principles and key links of point cloud model reconstruction technology based on the 3D photography were summarized. An algorithm of automatically eliminating irrelevant point clouds based on the coordinate transformation and bounding box was studied, and the effectiveness of this algorithm was validated using two case examples. The global point cloud registration and three local registration methods were studied. The detailed structures of components with different shapes and different positions were combined with engineering requirements for comparison. Considering the engineering requirements and the correspondence of registration method, three discriminant principles were proposed for the component dimensional inspection based on the color error nephogram and mathematical statistics method, including the discriminant principle based on mean and standard deviation of error, discriminant principle based on extreme value of error and comprehensive discrimination. The dimensions of a box culvert side wall and a pipe culvert side wall were inspected and evaluated by using these discriminant principles, based on comprehensive analysis of color error nephograms and error distributions. Research result shows that the three different discriminant principles are respectively suitable for the global, local, and global at first and then local inspections and evaluations of prefabricated components. Compared with the actual component, the average dimensional errors of length and width in the point cloud model of special-shaped concrete prefabricated component established by the 3D model reconstruction technology are about 1.5 mm. The 3D model reconstruction technology can replace the manual measurement method, can automatically eliminate irrelevant point clouds, and can facilitate a more stringent component dimensional inspection and evaluation meeting engineering requirements. 2 tabs, 16 figs, 31 refs.


[1] 李德仁.摄影测量与遥感的现状及发展趋势[J].武汉测绘科技大学学报,2000,25(1):1-6.
LI De-ren. Towards photogrammetry and remote sensing: status and future development[J]. Journal of Wuhan Technical University of Surveying and Mapping, 2000, 25(1): 1-6.(in Chinese)
[2] 陈 涛,方 亮.压气机叶轮的逆向重建及其模态分析[J].机械设计与制造,2019(1):202-204.
CHEN Tao, FANG Liang. Reverse reconstruction and modal analysis of compressor impeller[J]. Machinery Design and Manufacture, 2019(1): 202-204.(in Chinese)
[3] 段 伟,娄丽莎.基于逆向工程和三维打印的齿轮设计[J].科技通报,2019,35(1):157-159.
DUAN Wei, LOU Li-sha. Gear design based on reverse engineering and 3D printing[J]. Bulletin of Science and Technology, 2019, 35(1): 157-159.(in Chinese)
[4] 霍洪旭.大型复杂铸锻件三维扫描测量与数据处理方法研究[D].沈阳:沈阳工业大学,2017.
HUO Hong-xu. Large complex malleable cast a 3D-scanning point cloud data denoising and smoothing method research[D]. Shenyang: Shenyang University of Technology, 2017.(in Chinese)
[5] 吴婵玥.玉米叶片点云去噪软件的设计与实现[D].杨凌:西北农林科技大学,2017.
WU Chan-yue. Design and implementation for point cloud denoising software of corn leaf[D]. Yangling: Northwest A&F University, 2017.(in Chinese)
[6] 文 军,张 林,陈国平,等.基于计算机断层成像及逆向工程软件建立左心房憩室血流动力学有限元模型[J].生物医学工程学杂志,2018,35(6):870-876.
WEN Jun, ZHANG Lin, CHEN Guo-ping, et al.Construction of finite element model of left atrial diverticulum based on computed tomography and reverse engineering softwares[J]. Journal of Biomedical Engineering, 2018, 35(6): 870-876.(in Chinese)
[7] 任伟中,寇新建,凌浩美.数字化近景摄影测量在模型试验变形测量中的应用[J].岩石力学与工程学报,2004,23(3):436-440.
REN Wei-zhong, KOU Xin-jian, LING Hao-mei. Application of digital close-range photogrammetry in deformation measurement of model test[J]. Chinese Journal of Rock Mechanics and Engineering, 2004, 23(3): 436-440.(in Chinese)
[8] ELTNER A, KAISER A, ABELLAN A, et al. Time lapse structure-from-motion photogrammetry for continuous geomorphic monitoring[J]. Earth Surface Processes and Landforms, 2017, 42(14): 2240-2253.
[9] VALENÇA J, CARMO R N F. Method for assessing beam column joints in RC structures using photogrammetric computer vision[J]. Structural Control and Health Monitoring, 2017, 24(11): e2013.
[10] AHMADI F F. Integration of industrial videogrammetry and artificial neural networks for monitoring and modeling the deformation or displacement of structures[J]. Neural Computing and Applications, 2017, 28(12): 3709-3716.
[11] YANG D M, CHAO C F, HUANG K S, et al. Image-based 3D scene reconstruction and exploration in augmented reality[J]. Automation in Construction, 2013, 33: 48-60.
[12] BALAGUER-PUIG M, MARQUÉS-MATEU Á, LUIS LERMA J, et al. Estimation of small-scale soil erosion in laboratory experiments with structure from motion photogrammetry[J]. Geomorphology, 2017, 295: 285-296.
[13] DIAS-DA-COSTA D, VALENÇA J, JLIO E, et al. Crack propagation monitoring using an image deformation approach[J]. Structural Control and Health Monitoring, 2017, 24(10):e1973.
[14] 杨璐璟.点云数据的压缩算法研究——以数字地质博物馆为例[D].长沙:中南大学,2014.
YANG Lu-jing. Research on compression algorithm of point cloud data-taking digital geological museum as an example[D]. Changsha: Central South University, 2014.(in Chinese)
[15] 陈艳雷.基于逆向工程的扫描点云数据预处理技术研究[D].郑州:河南工业大学,2018.
CHEN Yan-lei.Research on scan point clouds data preprocessing techniques based on reverse engineering[D]. Zhengzhou: Henan University of Technology, 2018.(in Chinese)
[16] 付德敏.各向异性多边滤波在三维点云去噪中的应用研究[D].秦皇岛:燕山大学,2017.
FU De-min.Application research of anisotropic multilateral filter in 3D point cloud denoising[D]. Qinhuangdao: Yanshan University, 2017.(in Chinese)
[17] 史皓良.三维点云数据的去噪和特征提取算法研究[D].南昌:南昌大学,2017.
SHI Hao-liang. Study on denoising and feature extraction of 3D point cloud data[D]. Nanchang: Nanchang University, 2017.(in Chinese)
[18] 陈伟华.逆向工程中三维点云数据处理精度分析与研究[D].郑州:河南工业大学,2018.
CHEN Wei-hua. Analysis and research on accuracy of 3D point cloud data processing in reverse engineering[D]. Zhengzhou: Henan University of Technology, 2018.(in Chinese)
[19] CHOUDHURY P, TUMBLIN J. The trilateral filter for high contrast images and meshes[C]∥The Eurographics Association. Proceedings of the 14th Eurographics Workshop on Rendering Techniques. Leuven: The Eurographics Association, 2003: DOI: 10.1145/1198555.1198565.
[20] DESBRUN M, DURAND F, JONES T R. Non-iterative,
feature-preserving mesh smoothing[J]. ACM Transactions on Graphics, 2003, 22(3): 943-949.
[21] DRORI I, COHEN-OR D, FLEISHMAN S. Bilateral mesh denoising[J]. ACM Transactions on Graphics, 2003, 22(3): 950-953.
[22] 刘 鹏,陈 颖,罗小勇,等.装配式建筑混凝土构件公差控制国内外标准分析[J].建筑科学与工程学报,2018,35(6):41-49.
LIU Peng, CHEN Ying, LUO Xiao-yong, et al. Tolerance control analysis of concrete member for prefabricated construction in domestic and international standards[J]. Journal of Architecture and Civil Engineering, 2018, 35(6): 41-49.(in Chinese)
[23] 李迎吉.核电零部件制造过程质量管理与控制系统研究与开发[D].无锡:江南大学,2012.
LI Ying-ji. Research and development of quality management and control system for manufacturing process of nuclear parts[D]. Wuxi: Jiangnan University, 2012.(in Chinese)
[24] 陆建新,冯长胜,党保卫.复杂X形节点钢柱外观尺寸的测量验收[J].施工技术,2008,37(增):162-163.
LU Jian-xin, FENG Chang-sheng, DANG Bao-wei. Measurement acceptance of steel column appearance size with complicated X shaped joints[J]. Construction Technology, 2008, 37(S): 162-163.(in Chinese)
[25] 王永强.基于单相片的视觉测量技术研究[D].郑州:解放军信息工程大学,2017.
WANG Yong-qiang. On monocular vision measurement technique based on single photo[D]. Zhengzhou:PLA Information Engineering University, 2017.(in Chinese)
[26] 岳立廷.多视角三维重建算法的研究[D].天津:河北工业大学,2011.
YUE Li-ting.Research on 3D reconstruction algorithm from multi-view images[D]. Tianjin: Hebei University of Technology, 2011.(in Chinese)
[27] 高瞻宇,顾营迎,刘宇航,等.采用简化Brown模型及改进BFGS法的相机自标定[J].光学精密工程,2017,25(9):2532-2540.
GAO Zhan-yu, GU Ying-ying, LIU Yu-hang, et al. Self-calibration based on simplified Brown non-linear camera model and modified BFGS algorithm[J]. Optics and Precision Engineering, 2017, 25(9): 2532-2540.(in Chinese)
[28] 黄高锋,陈 义,符宏伟.基于特征点匹配及提纯的点云配准算法[J].测绘与空间地理信息,2019,42(2):199-202.
HUANG Gao-feng, CHEN Yi, FU Hong-wei. Point cloud registration algorithm based on keypoints matching and purification[J]. Geomatics and Spatial Information Technology, 2019, 42(2): 199-202.(in Chinese)
[29] HÄNSCH R, WEBER T, HELLWICH O. Comparison of 3D interest point detectors and descriptors for point cloud fusion[J]. Remote Sensing and Spatial Information Sciences, 2014, 2/3: 57-64.
[30] BESL P J, MCKAY H D. A method for registration of 3-D shapes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, 14(2): 239-256.
[31] 刘承香,阮双琛,刘繁明,等.基于迭代最近点算法的地形匹配算法可靠性分析[J].深圳大学学报(理工版),2005,22(1):22-26.
LIU Cheng-xiang, RUAN Shuang-chen, LIU Fan-ming, et al. Analysis on the reliability of terrain matching algorithm based on ICP[J]. Journal of Shenzhen University(Science and Engineering), 2005, 22(1): 22-26.(in Chinese)


Last Update: 2021-06-01