基于三维模型重构技术的公路预制构件尺寸检验评价方法

石雪飞; 徐梓齐; 朱荣; 傅青松

doi:10.19818/j.cnki.1671-1637.2021.02.006

基于三维模型重构技术的公路预制构件尺寸检验评价方法

doi: 10.19818/j.cnki.1671-1637.2021.02.006

1.
同济大学土木工程学院，上海 200092
2.
上海同济检测技术有限公司，上海 200092

基金项目:

国家重点研发计划项目 2018YFC0809606

详细信息

作者简介:
石雪飞(1964-)，男，江苏泰州人，同济大学教授，工学博士，从事桥梁工程施工与信息技术研究

通讯作者:
徐梓齐(1996-)，男，黑龙江齐齐哈尔人，同济大学工学博士研究生

中图分类号: U449.34
计量
- 文章访问数: 549
- HTML全文浏览量: 264
- PDF下载量: 98
- 被引次数: 0
出版历程
- 收稿日期: 2020-10-05
- 刊出日期: 2021-04-01

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

1.
College of Civil Engineering, Tongji University, Shanghai 200092, China
2.
Shanghai Tongji Testing Technology Co., Ltd., Shanghai 200092, China

Funds:

National Key Research and Development Program of China 2018YFC0809606

More Information

Author Bio:
SHI Xue-fei(1964-), male, professor, PhD, xfs@tongji.edu.cn

Corresponding author: XU Zi-qi(1996-), male, doctoral student, xuziqi@tongji.edu.cn

摘要

摘要: 为使公路工程异形混凝土预制构件的制造尺寸检验评价适应工业化建造要求，应用三维模型重构技术检验评价了异形混凝土预制构件尺寸，提出了高精度、自动化异形混凝土预制构件尺寸检验评价方法，包括三维模型重构、点云数据处理和检验评价体系3个环节；总结了基于三维摄影的点云模型重构技术的原理和关键环节，研究了基于坐标转换和包围盒的无关点云自动剔除算法，并通过2个实例验证了该算法的效果；研究了点云整体配准和3类局部配准方法，针对不同形状的构件和不同位置的细部构造，结合工程需求进行对照；考虑工程需求并与配准方法对应，提出了基于彩色误差云图和数理统计方法进行构件尺寸检验评价的3种判异原则，包括误差均值和标准差判异原则、误差极值判异原则、综合判异原则；综合分析彩色误差云图和误差分布，利用判异原则对箱型涵洞侧墙和管型涵洞侧墙实例的尺寸进行了检验评价。研究结果表明：3种判异原则分别适合对预制构件进行整体宏观、局部单项和先整体后局部的检验评价；采用三维模型重构技术建立的异形混凝土预制构件点云模型，与实际构件相比其长度和宽度的误差均值约为1.5 mm，三维模型重构技术可以替代人工测量；能够自动化剔除无关点云，并执行更为严格且符合工程需求的构件尺寸检验评价。
- 桥梁工程 /
- 异形混凝土预制构件 /
- 尺寸检验评价 /
- 三维模型重构 /
- 点云去噪 /
- 点云配准
Abstract: 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 evaluation on 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.
- bridge engineering /
- special-shaped concrete prefabricated component /
- dimensional inspection and evaluation /
- 3D model reconstruction /
- point cloud denoising /
- point cloud registration

HTML全文

图 1 基于三维重构技术的异形混凝土预制构件尺寸检验评价流程

Figure 1. Dimensional inspection and evaluation process of special-shaped concrete prefabricated components based on 3D reconstruction technology

下载: 全尺寸图片幻灯片

图 2 像素坐标系与图像坐标系

Figure 2. Pixel coordinate system and image coordinate system

下载: 全尺寸图片幻灯片

图 3 多张照片的点云拼接过程

Figure 3. Point cloud stitching process of multiple photos

下载: 全尺寸图片幻灯片

图 4 标记点示意

Figure 4. Schematic of mark points

下载: 全尺寸图片幻灯片

图 5 局部面配准示意

Figure 5. Schematics of local surface registration

下载: 全尺寸图片幻灯片

图 6 局部线配准示意

Figure 6. Schematics of local line registration

下载: 全尺寸图片幻灯片

图 7 局部角点配准示意

Figure 7. Schematics of local corner registration

下载: 全尺寸图片幻灯片

图 8 典型彩色误差云图

Figure 8. Typical color error nephogram

下载: 全尺寸图片幻灯片

图 9 典型误差分布

Figure 9. Typical error distribution

下载: 全尺寸图片幻灯片

图 10 预制涵洞构件实例(单位: cm)

Figure 10. Examples of prefabricated culvert components (unit: cm)

下载: 全尺寸图片幻灯片

图 11 无关点云剔除实例

Figure 11. Examples of irrelevant points elimination

下载: 全尺寸图片幻灯片

图 12 配准后的管涵点云和设计模型

Figure 12. Tube culvert point cloud and design model after registration

下载: 全尺寸图片幻灯片

图 13 箱涵侧墙整体检验评价实例

Figure 13. Example of global inspection and evaluation for side wall of box culvert

下载: 全尺寸图片幻灯片

图 14 箱涵侧墙底面检验评价实例

Figure 14. Example of bottom surface inspection and evaluation for side wall of box culvert

下载: 全尺寸图片幻灯片

图 15 箱涵侧墙左侧面检验评价实例

Figure 15. Example of left side surface inspection and evaluation for side wall of box culvert

下载: 全尺寸图片幻灯片

图 16 管涵侧墙整体检验评价实例

Figure 16. Example of global inspection and evaluation for side wall of tube culvert

下载: 全尺寸图片幻灯片

表 1 基于误差均值和标准差的判异原则

Table 1. Discriminant principle based on mean and standard deviation of error

项次	项目	允许值/mm
1	μ	10
2	3σ	20

下载: 导出CSV

表 2 三维重构尺寸与人工测量尺寸比较

Table 2. Comparison between 3D reconstruction and manual measurement dimensions

项目名称	项目编号	第1次人工测量/m	第2次人工测量/m	第3次人工测量/m	第4次人工测量/m	第5次人工测量/m	实际尺寸/m	重构尺寸/m	误差/m	平均误差/m
长	1	0.285 6	0.285 3	0.285 2	0.285 2	0.285 5	0.285 4	0.285 7	0.000 3	0.001 5
	2	0.286 7	0.285 6	0.285 0	0.285 2	0.285 1	0.285 5	0.286 0	0.000 5
	3	0.283 0	0.284 0	0.283 9	0.283 7	0.283 9	0.283 7	0.286 2	0.002 5
	4	0.288 9	0.287 1	0.287 8	0.287 3	0.288 0	0.287 8	0.290 4	0.002 6
宽	1	0.283 0	0.283 8	0.283 4	0.283 3	0.283 9	0.283 5	0.284 5	0.001 0	0.001 4
	2	0.283 3	0.284 1	0.284 0	0.284 1	0.284 0	0.283 9	0.284 1	0.000 2
	3	0.285 2	0.284 3	0.284 6	0.285 0	0.285 0	0.284 8	0.287 1	0.002 3
	4	0.286 7	0.286 6	0.287 0	0.286 9	0.286 7	0.286 8	0.289 0	0.002 2

下载: 导出CSV

参考文献(31)

[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. https://www.cnki.com.cn/Article/CJFDTOTAL-WHCH200001000.htm 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) https://www.cnki.com.cn/Article/CJFDTOTAL-WHCH200001000.htm
[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. doi: 10.3969/j.issn.1001-3997.2019.01.052 CHEN Tao, FANG Liang. Reverse reconstruction and modal analysis of compressor impeller[J]. Machinery Design and Manufacture, 2019(1): 202-204. (in Chinese) doi: 10.3969/j.issn.1001-3997.2019.01.052
[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. https://www.cnki.com.cn/Article/CJFDTOTAL-KJTB201901038.htm 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) https://www.cnki.com.cn/Article/CJFDTOTAL-KJTB201901038.htm
[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. https://www.cnki.com.cn/Article/CJFDTOTAL-SWGC201806007.htm 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) https://www.cnki.com.cn/Article/CJFDTOTAL-SWGC201806007.htm
[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. doi: 10.3321/j.issn:1000-6915.2004.03.014 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) doi: 10.3321/j.issn:1000-6915.2004.03.014
[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. doi: 10.1002/esp.4178
[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. doi: 10.1002/stc.2013
[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. doi: 10.1007/s00521-016-2255-2
[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. doi: 10.1016/j.autcon.2012.09.017
[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. doi: 10.1016/j.geomorph.2017.04.035
[13]	DIAS-DA-COSTA D, VALENÇA J, JÚLIO E, et al. Crack propagation monitoring using an image deformation approach[J]. Structural Control and Health Monitoring, 2017, 24(10): e1973. doi: 10.1002/stc.1973
[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. doi: 10.1145/882262.882367
[21]	DRORI I, COHEN-OR D, FLEISHMAN S. Bilateral mesh denoising[J]. ACM Transactions on Graphics, 2003, 22(3): 950-953. doi: 10.1145/882262.882368
[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. doi: 10.3969/j.issn.1673-2049.2018.06.006 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) doi: 10.3969/j.issn.1673-2049.2018.06.006
[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. https://www.cnki.com.cn/Article/CJFDTOTAL-SGJS200805052.htm 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) https://www.cnki.com.cn/Article/CJFDTOTAL-SGJS200805052.htm
[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. https://www.cnki.com.cn/Article/CJFDTOTAL-GXJM201709033.htm 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) https://www.cnki.com.cn/Article/CJFDTOTAL-GXJM201709033.htm
[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. doi: 10.3969/j.issn.1672-5867.2019.02.059 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) doi: 10.3969/j.issn.1672-5867.2019.02.059
[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. http://adsabs.harvard.edu/abs/2014ISPAn.II3...57H
[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. doi: 10.1109/34.121791
[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. doi: 10.3969/j.issn.1000-2618.2005.01.005 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) doi: 10.3969/j.issn.1000-2618.2005.01.005