| Citation: | WANG Xiao-ming, DENG Lu, SHI Yi-zhe, ZHANG Tong, YUAN Tong, KOU Yu, LI Xiao, LIU Yu-xuan. Intelligent dimensional inspection method for steel box arch prefabricated components based on Harris features and NDT-ICP algorithm[J]. Journal of Traffic and Transportation Engineering, 2024, 24(1): 158-170. doi: 10.19818/j.cnki.1671-1637.2024.01.010
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In response to the challenges of low efficiency and high cost of traditional manual dimensional inspection in face of massive bridge prefabricated components during the bridge construction, and to break through the accuracy and efficiency bottlenecks of existing data processing algorithms in the intelligent dimensional inspection using the terrestrial laser scanning (TLS) technology, an intelligent dimensional inspection framework for bridge steel prefabricated components was established based on the building information modeling (BIM)-TLS, including two links: geometric dimensional inspection and digital pre-assembly of components. The BIM point cloud processing technology was customized, and the reference point cloud model was constructed. The point cloud data were preprocessed by using the straight-through filtering, statistical outlier removal (SOR) filtering, voxel grid (VG), and other algorithms. The dimensional inspection index evaluation based on the k-nearest neighbor (kNN) algorithm was realized. Through the 3D-Harris feature point inspection, normal distributions transform (NDT) coarse registration, and iterative closet point (ICP) fine registration, a fast registration intelligent dimensional inspection strategy based on the Harris feature and NDT-ICP algorithm was proposed and applied to the intelligent dimensional inspection of steel box arch prefabricated components of a large-span arch beam composite structure in combination with the engineering requirements. Research results show that the maximum deviations of the proposed intelligent inspection method for the dimensional inspection of two steel box arches at adjacent segments are 1.689 and 1.571 mm, respectively, and meet the requirement of the manufacturing deviation (less than 2 mm). Compared with the traditional NDT-ICP algorithm, the proposed method improves the overall registration accuracy of the point cloud by 35.3% and the efficiency by 61.88%. It can be seen that the method is efficient, and the results are accurate. It promotes the intelligence of the geometric dimensional inspection of steel prefabricated components. Based on the method, the maximum inspection assembly deviation of the digital pre-assembly monitoring point for the arch rib is 1.953 3 mm, and meets the requirement of the assembly deviation (less than 2 mm). The method realizes the accurate deviation inspection. It provides a good guarantee for the smooth erection of subsequent bridge positions and a reference for dimensional inspections of similar structures.
| [1] |
RASHIDI M, MOHAMMADI M, KIVI S S, et al. A decade of modern bridge monitoring using terrestrial laser scanning: review and future directions[J]. Remote Sensing, 2020, 12(22): 3796. doi: 10.3390/rs12223796
|
| [2] |
刘占省, 孙啸涛, 史国梁. 智能建造在土木工程施工中的应用综述[J]. 施工技术(中英文), 2021, 50(13): 40-53. https://www.cnki.com.cn/Article/CJFDTOTAL-SGJS202113006.htm
LIU Zhan-sheng, SUN Xiao-tao, SHI Guo-liang. Summary of application of intelligent construction in civil engineering construction[J]. Construction Technology, 2021, 50(13): 40-53. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-SGJS202113006.htm
|
| [3] |
CHEN Zhi-ping, ZHANG Wen-dian, HUANG Rong-gang, et al. 3D model-based terrestrial laser scanning (TLS) observation network planning for large-scale building facades[J]. Automation in Construction, 2022, 144: 104594. doi: 10.1016/j.autcon.2022.104594
|
| [4] |
WANG Yin-gang, HE Xiong-jun, HE Jia, et al. Virtual trial assembly of steel structure based on BIM platform[J]. Automation in Construction, 2022, 141: 104395. doi: 10.1016/j.autcon.2022.104395
|
| [5] |
DABOUS S A, FEROZ S. Condition monitoring of bridges with non-contact testing technologies[J]. Automation in Construction, 2020, 116: 103224. doi: 10.1016/j.autcon.2020.103224
|
| [6] |
卢颖. 基于三维激光扫描的桥梁检测技术应用研究[D]. 长春: 吉林大学, 2017.
LU Ying. Application research on the bridge detection technology based on the three-dimensional laser scanning[D]. Changchun: Jilin University, 2017. (in Chinese)
|
| [7] |
鲍跃全, 李惠. 人工智能时代的土木工程[J]. 土木工程学报, 2019, 52(5): 1-11. https://www.cnki.com.cn/Article/CJFDTOTAL-TMGC201905001.htm
BAO Yue-quan, LI Hui. Artificial intelligence for civil engineering[J]. China Civil Engineering Journal, 2019, 52(5): 1-11. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-TMGC201905001.htm
|
| [8] |
NOGHABAEI M, LIU Ya-jie, HAN K. Automated compatibility checking of prefabricated components using 3D as-built models and BIM[J]. Automation in Construction, 2022, 143: 104566. doi: 10.1016/j.autcon.2022.104566
|
| [9] |
REBOLJ D, PU AČG KO Z, BABI AČG N AČG, et al. Point cloud quality requirements for Scan-vs-BIM based automated construction progress monitoring[J]. Automation in Construction, 2017, 84: 323-334. doi: 10.1016/j.autcon.2017.09.021
|
| [10] |
梁栋, 蒲洁, 赵恺, 等. 钢桥塔的点云虚拟装配及其整体线形控制方法[J]. 天津大学学报(自然科学与工程技术版), 2022, 55(8): 828-838. https://www.cnki.com.cn/Article/CJFDTOTAL-TJDX202208007.htm
LIANG Dong, PU Jie, ZHAO Kai, et al. Point cloud virtual assembly of steel bridge towers and its overall linear control method[J]. Journal of Tianjin University (Science and Technology), 2022, 55(8): 828-838. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-TJDX202208007.htm
|
| [11] |
杨莎莎, 郝龙, 宋成年, 等. 基于BIM和LST的结构外观尺寸量测方法研究[J]. 武汉大学学报(工学版), 2023, 56(4): 455-462. https://www.cnki.com.cn/Article/CJFDTOTAL-WSDD202304009.htm
YANG Sha-sha, HAO Long, SONG Cheng-nian, et al. Research on the structure appearance dimension inspection method based on BIM and LST[J]. Engineering Journal of Wuhan University, 2023, 56(4): 455-462. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-WSDD202304009.htm
|
| [12] |
LIU Jin-dian, ZHANG Qi-lin, WU Jie, et al. Dimensional accuracy and structural performance assessment of spatial structure components using 3D laser scanning[J]. Automation in Construction, 2018, 96: 324-336. doi: 10.1016/j.autcon.2018.09.026
|
| [13] |
刘金典, 张其林, 张金辉. 基于建筑信息模型和激光扫描的装配式建造管理与质量控制[J]. 同济大学学报(自然科学版), 2020, 48(1): 33-41. https://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ202001005.htm
LIU Jin-dian, ZHANG Qi-lin, ZHANG Jin-hui. Construction management and quality control of prefabricated building based on BIM and 3D laser scanning[J]. Journal of Tongji University (Natural Science), 2020, 48(1): 33-41. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ202001005.htm
|
| [14] |
KIM M K, THEDJA J P P, WANG Qian. Automated dimensional quality assessment for formwork and rebar of reinforced concrete components using 3D point cloud data[J]. Automation in Construction, 2020, 112: 103077. doi: 10.1016/j.autcon.2020.103077
|
| [15] |
齐宏拓, 刘界鹏, 程国忠, 等. 基于点云数据的大型复杂钢结构智能化施工方法[J]. 土木工程学报, 2024, 57(1): 65-75. https://www.cnki.com.cn/Article/CJFDTOTAL-TMGC202401007.htm
QI Hong-tuo, LIU Jie-peng, CHENG Guo-zhong, et al. Intelligent construction of large and complex steel structure based on point cloud data[J]. China Civil Engineering Journal, 2024, 57(1): 1065-1075. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-TMGC202401007.htm
|
| [16] |
陆军, 陈坤, 范哲君. 点邻域尺度差异描述的点云配准算法[J]. 国防科技大学学报, 2021, 43(3): 128-134. https://www.cnki.com.cn/Article/CJFDTOTAL-GFKJ202103015.htm
LU Jun, CHEN Kun, FAN Zhe-jun. Point cloud registration algorithm based on scale difference descriptor of point neighborhood[J]. Journal of National University of Defense Technology, 2021, 43(3): 128-134. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GFKJ202103015.htm
|
| [17] |
CHATTERJEE S. ISSAC K K. Viewpoint planning and 3D image stitching algorithms for inspection of panels[J]. NDT and E International, 2023, 137: 102837. doi: 10.1016/j.ndteint.2023.102837
|
| [18] |
朱明芳, 程效军, 李金涛, 等. 基于底面特征匹配的钢结构桥梁虚拟预拼装[J]. 北京测绘, 2022, 36(2): 168-172. https://www.cnki.com.cn/Article/CJFDTOTAL-BJCH202202012.htm
ZHU Ming-fang, CHENG Xiao-jun, LI Jin-tao, et al. A digital virtual pre-assembly method of steel structure bridge based on features matching of bottom surface[J]. Beijing Surveying and Mapping, 2022, 36(2): 168-172. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-BJCH202202012.htm
|
| [19] |
马永强. 改进ICP算法在桥梁三维激光扫描数据配准中的应用研究[J]. 测绘与空间地理信息, 2020, 43(11): 173-176. https://www.cnki.com.cn/Article/CJFDTOTAL-DBCH202011047.htm
MA Yong-qiang. Application research of improved ICP algorithm on bridge 3D laser scanning data registration[J]. Geomatics and Spatial Information Technology, 2020, 43(11): 173-176. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DBCH202011047.htm
|
| [20] |
胡绍兰, 黄凤玲, 张国兴, 等. 基于BIM+点云数据的钢结构质量智能检测方法[J]. 土木工程与管理学报, 2022, 39(5): 28-33, 49. https://www.cnki.com.cn/Article/CJFDTOTAL-WHCJ202205004.htm
HU Shao-lan, HUANG Feng-ling, ZHANG Guo-xing, et al. Steel structure quality intelligent detection method based on BIM+point cloud data[J]. Journal of Civil Engineering and Management, 2022, 39(5): 28-33, 49. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-WHCJ202205004.htm
|
| [21] |
ZOTKIN S P, IGNATOVA E V, ZOTKINA I A. The organization of Autodesk Revit software interaction with applications for structural analysis[J]. Procedia Engineering, 2016, 153: 915-919.
|
| [22] |
袁华, 庞建铿, 莫建文. 基于体素化网格下采样的点云简化算法研究[J]. 电视技术, 2015, 39(17): 43-47. https://www.cnki.com.cn/Article/CJFDTOTAL-DSSS201517012.htm
YUAN Hua, PANG Jian-keng, MO Jian-wen. Research on simplification algorithm of point cloud based on voxel grid[J]. Video Engineering, 2015, 39(17): 43-47. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DSSS201517012.htm
|
| [23] |
石雪飞, 徐梓齐, 朱荣, 等. 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[J]. 交通运输工程学报, 2021, 21(2): 66-81. doi: 10.19818/j.cnki.1671-1637.2021.02.006
SHI Xue-fei, XU Zi-qi, ZHU Rong, et al. Dimensional inspection and evaluation method of highway prefabricated components based on 3D model reconstruction technology[J]. Journal of Traffic and Transportation Engineering, 2021, 21(2): 66-81. (in Chinese) doi: 10.19818/j.cnki.1671-1637.2021.02.006
|
| [24] |
SHAO Yu-yuan, TONG Guo-feng, PENG Hao. Mining local geometric structure for large-scale 3D point clouds semantic segmentation[J]. Neurocomputing, 2022, 500: 191-202.
|
| [25] |
ZHU Tian-yu, MA Xiao-dan, GUAN Hai-ou, et al. A calculation method of phenotypic traits based on three-dimensional reconstruction of tomato canopy[J]. Computers and Electronics in Agriculture, 2023, 204: 107515.
|
| [26] |
SHI Xiu-ying, PENG Jian-jun, LI Ji-ping, et al. The iterative closest point registration algorithm based on the normal distribution transformation[J]. Procedia Computer Science, 2019, 147: 181-190.
|
| [27] |
贾薇, 舒勤, 黄燕琴. 基于FPFH的点云特征点提取算法[J]. 机算机应用与软件, 2020, 37(7): 165-169, 245. https://cdmd.cnki.com.cn/Article/CDMD-10147-1024319775.htm
JIA Wei, SHU Qin, HUANG Yan-qin. Feature point extraction algorithm of point cloud based on FPFH[J]. Computer Applications and Software, 2020, 37(7): 165-169, 245. (in Chinese) https://cdmd.cnki.com.cn/Article/CDMD-10147-1024319775.htm
|
| [28] |
仲宇, 白钒, 刘勇, 等. 基于改进3D-Harris角点检测算法的电厂地下管廊点云拼接方法研究[J]. 热力发电, 2023, 52(1): 89-97. https://www.cnki.com.cn/Article/CJFDTOTAL-RLFD202301009.htm
ZHONG Yu, BAI Fan, LIU Yong, et al. Study on point cloud splicing method of underground pipe gallery in power plants based on improved 3D-Harris operator[J]. Thermal Power Generation, 2023, 52(1): 89-97. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-RLFD202301009.htm
|
| [29] |
张晓, 张爱武, 王致华. 基于改进正态分布变换算法的点云配准[J]. 激光与光电子学进展, 2014, 51(4): 041002. https://www.cnki.com.cn/Article/CJFDTOTAL-JGDJ201404016.htm
ZHANG Xiao, ZHANG Ai-wu, WANG Zhi-hua. Point cloud registration based on improved normal distribution transform algorithm[J]. Laser and Optoelectronics Progress, 2014, 51(4): 041002. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JGDJ201404016.htm
|
| [30] |
GAO Hui-ping, XU Gui-li, ZHANG Zi-li, et al. A novel probability iterative closest point with normal vector algorithm for robust rail profile registration[J]. Optik—International Journal for Light and Electron Optics, 2021, 243: 166936.
|
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