3D reconstruction and visualization for laser drilling hole on rock based on line laser scanning
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摘要: 激光钻进岩石形成的钻孔的孔形较为复杂，具有较小的孔直径和较高的孔壁粗糙度，使得利用传统方法进行钻孔尺寸的测量较为困难。为了精确钻孔测量和方便孔形研究，提出了一种基于线激光扫描及逆向建模的钻孔建模方法。首先，搭建了线激光扫描平台，建立了空间坐标系，以获取钻孔的三维坐标，构建了钻孔的初始点云数据。其次，在MATLAB中对获取的点云数据进行无效点移除及多视角点云配准，其中，无效点移除利用顺序查找法实现，多视角点云配准则基于迭代最近点（ICP）算法，包括初始配准和精确配准两个阶段。最后，基于Delaunay三角网格划分及曲面重建算法，实现了钻孔模型的重建和可视化。此外，还采用滴液法和切割法进行实际钻孔容积值测量及钻孔轮廓线获取，并与由点云重建的钻孔模型上获取的测算结果进行对比分析，以验证所述方法建立的钻孔模型的精度。结果表明：重建的钻孔模型与实际钻孔之间的误差小于4%，重建的模型能够满足激光岩石钻进钻孔的测量要求，证实了所述方法的可行性。与传统测量方法相比，所述方法属于非接触、非破坏性方法，可重复性测量。Abstract: The laser drilling hole on rock has a complex pattern, characterized with a generally small diameter and high roughness, so it is difficult to measure the parameters by traditional methods.Therefore, in order to precisely detect the drilling hole and expediently study the shape of the hole, a model of the laser drilling hole based on line laser scanning and reserve modeling is proposed.Specifically, to get the 3D coordinate of the drilling hole, which consists of the original point cloud, a line laser scanning stage is designed and the spatial coordinate system is established.Then, point cloud processing, including the valid points removal and point cloud registration, is implemented in MATLAB, and the removal of invalid points is realized by sequential search, also, based on the iterative closest point(ICP) algorithm, the multi-view point cloud registration is divided into two stages: the initial registration and the precise registration.Finally, based on Delaunay triangulation and surface reconstruction, the model reconstruction and 3D visualization of the drilling hole are accomplished, which provides a good matrix for drilling hole measurement.What's more, compared with the results from the model reconstructed, the titration test and cutting method are used to measure the volume and obtain the contour line of the real drilling hole, to evaluate the accuracy of the drilling hole model.The experimental results show that the error between the models reconstructed and the real drilling holes is less than 4%, hence the reconstructed model can meet the requirements of measuring the parameters of the laser drilling hole on the rock, and the method proposed is feasible.Furthermore, this approach belongs to a non-contact and non-destructive detection method accompanied with good repeatability in comparison with existing methods.
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Key words:
- laser drilling hole /
- line laser scanning /
- point cloud /
- model reconstruction /
- visualization
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图 3 三维坐标系建立及坐标值获取
Figure 3. Establishment of the 3D Coordinate system acquisition of the coordinate value
图 6 多视角扫描获得的钻孔点云
a.贴有辅助标志点的钻孔；b.视角1得到的点云；c.视角2得到的点云
Figure 6. Point cloud of the drilling hole from multi-view scanning
图 9 钻孔点云的Delaunay三角网格划分
a.钻孔点云及X-Y上的Delaunay三角网格；b.三维钻孔Delaunay三角网格
Figure 9. Delaunay triangulation mesh of the point cloud of the drilling hole
图 11 钻孔模型重建
a.岩石上的真实钻孔; b.所建立的钻孔模型
Figure 11. Implementation examples of model reconstruction of the drilling hole
图 12 点云数据与模型间的误差分析
Figure 12. Deviation analysis between the point cloud data and the reconstructed model
图 14 岩石上钻孔容积测量
a.试验所用的滴定管和食用油；b.充满食用油的钻孔
Figure 14. Volume measurement on the rock drilling hole
图 15 模型上钻孔容积测量
a.布尔交集运算；b.模型上测得的钻孔的容积
Figure 15. Volume measurement of the drilling hole on the model
图 18 各轮廓线对在同一坐标系下的拟合结果
Figure 18. Contour lines pairs matching results in the same coordinate system
表 1 钻孔容积测量结果
Table 1. Measurement results of the volume of the drilling holes
孔序号 1# 2# 3# 4# 5# 6# VT/mm3 278 160 54 260 180 236 VM/mm3 287.08 156.63 52.86 264.59 184.47 241.59 EA/mm3 -9.08 3.37 1.14 -4.59 -4.47 5.59 ER/% 3.27 2.11 2.16 1.77 2.48 2.37 
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表 2 轮廓线匹配结果
Table 2. Results of contour lines matching
轮廓线对序号 Fréchet距离值δdF/mm Pearson相关系数ρX, Y Ⅰ 0.163 0.987 Ⅱ 0.248 0.975 Ⅲ 0.081 0.992 Ⅳ 0.290 0.971 Ⅴ 0.196 0.979 Ⅵ 0.187 0.979 Ⅶ 0.163 0.985 Ⅷ 0.274 0.973 Ⅸ 0.186 0.974 Ⅹ 0.162 0.982
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[1] Xu Z Y, Yamashita Y, Reed C B. Two-dimensional modeling of laser spallation drilling of rocks[C]//ICALEO 2005: 24th International Congress on Laser Materials Processing and Laser Microfabrication, 2005. [2] 李璐. 激光辅助钻井破岩机理及可钻性研究[D]. 山东: 中国石油大学, 2015.Li L. Mechanism of removing rock by laser and the study on drillability[D]. Shandong: China University of Petroleum, 2015(in Chinese with English abstract). [3] Bharatish A, Kumar B K, Rajath R, et al. Investigation of effect of CO2 laser parameters on drilling characteristics of rocks encountered during mining-ScienceDirect[J]. Journal of King Saud University-Engineering Sciences, 2019, 31(4): 395-401. doi: 10.1016/j.jksues.2017.12.003 [4] Li M Y, Han B, Zhang S Y, et al. Investigation into Laser Perforation of Rock for Petroleum Exploitation[J]. Lasers in Engineering, 2018, 41(1): 73-99. [5] Zhang H, Yin S D. Poroelastoplastic borehole modeling by tangent stiffness matrix method[J]. International Journal of Geomechanics, 2020, 20(3): 1-11. http://www.sciencedirect.com/science/article/pii/S2405656120300808 [6] 张建芳, 范柱国. 基于ArcGIS的钻孔三维可视化展示及地质体的建模过程[J]. 中国水运, 2020, 20(4): 35-36. https://www.cnki.com.cn/Article/CJFDTOTAL-ZSUX202004017.htmZhang J F, Fan Z G. 3D visualization display of borehole and modeling process of geological body based on ArcGIS[J]. China Water Transport, 2020, 20(in Chinese with English abstrac). https://www.cnki.com.cn/Article/CJFDTOTAL-ZSUX202004017.htm [7] 李程, 吴志春, 杨羿, 等. 基于GOCAD的钻孔数据建模方法与实例研究[J]. 江西科学, 2019, 37(1): 125-130, 135. https://www.cnki.com.cn/Article/CJFDTOTAL-JSKX201901026.htmLi C, Wu Z C, Yang Y, et al. Drilling data modeling method and case study based on GOCAD[J]. Jiangxi Science, 2019, 37(1): 125-130, 135(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-JSKX201901026.htm [8] 张夏林, 师志龙, 吴冲龙, 等. 基于移动设备的野外地质大数据智能采集和可视化技术[J]. 地质科技通报, 2020, 39(4): 21-28. http://dzkjqb.cug.edu.cn/CN/abstract/abstract9995.shtmlZhang X L, Shi Z L, Wu C L. Intelligent data acquisition and visualizati-on technology of field geology based on mobile devices[J]. Bulletin of Geological Science and Technology, 2020, 39(4): 21-28(in Chinese with English abstract). http://dzkjqb.cug.edu.cn/CN/abstract/abstract9995.shtml [9] 万剑华, 王朝, 刘善伟, 等. 倾斜摄影测量构建地质数字露头[J]. 地质科技情报, 2019, 38(1): 258-264. https://www.cnki.com.cn/Article/CJFDTOTAL-DZKQ201901029.htmWan J H, Wang C, Liu S W, et al. Reconsting geological digital outcrops with oblique photogrammetry[J]. Geological Science and Technology Information, 2019, 38(1): 258-264(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DZKQ201901029.htm [10] Lemon A M, Jones N L. Building solid models from boreholes and user defined cross section[J]. Computers&Geosciences, 2003, 29(5): 547-555. http://www.sciencedirect.com/science/article/pii/S0098300403000517 [11] 田宜平, 吴冲龙, 翁正平, 等. 地质大数据可视化关键技术探讨[J]. 地质科技通报, 2020, 39(4): 29-36. http://dzkjqb.cug.edu.cn/CN/abstract/abstract9996.shtmlTian Y P, Wu C L, Weng Z P. Key technologies of geological big data visualization[J]. Bulletin of Geological Science and Technology, 2020, 39(4): 29-36(in Chinese with English abstract). http://dzkjqb.cug.edu.cn/CN/abstract/abstract9996.shtml [12] 迟克浩, 陈梦雯, 吴彦达, 等. 基于双三角测距原理的双线激光三维扫描系统的研制[J]. 物理与工程, 2019, 29(6): 71-76. https://www.cnki.com.cn/Article/CJFDTOTAL-GKWL201906013.htmChi K H, Chen M W, Wu Y D, et al. Development of three-dimensional scanner with double line lasers based on triangle measurement method of distance[J]. Physics and Engineering, 2019, 29(6): 71-76(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-GKWL201906013.htm [13] Zhao Y H, Supri T B M, Song Y, et al. A new static method of calibration for low-cost laser triangulation systems[J]. Measurement, 2020, 156: 1-9. http://www.sciencedirect.com/science/article/pii/S0263224120301500 [14] Yao B, Cai Z, Lu J, et al. Novel laser triangulation measurement method for screw rotor profile under multi-factor constraints[J]. Measurement, 2020, 152: 1-14. http://www.sciencedirect.com/science/article/pii/S0263224119311819 [15] 李现坤, 曾德标, 孟华林, 等. 基于2D激光扫描的基准检测技术研究[J]. 机械制造与自动化, 2020, 49(1): 195-197. https://www.cnki.com.cn/Article/CJFDTOTAL-ZZHD202001053.htmLi X K, Zeng D B, Meng H L, et al. Research on benchmark detection technology based on 2D line laser scanning[J]. Machine Building & Automation, 2020, 49(1): 195-197(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-ZZHD202001053.htm [16] Yao C L, Ying L, Rui S, et al. Multi-view point cloud registration with adaptive convergence threshold and its application in 3D model retrieval[J]. Multimedia Tools and Applications, 2019, 79(1): 793-810. doi: 10.1007/s11042-019-7524-5 [17] 薛耀红, 赵建平, 蒋振刚, 等. 点云数据配准及曲面细分技术[M]. 北京: 国防工业出版社, 2011.Xue Y H, Zhao J P, Jiang Z G, et al. Point cloud data registration and surface subdivision[M]. Beijing: Nation Defense Industry Press, 2011(in Chinese). [18] 徐兆阳. 三维重建中的点云配准技术研究[D]. 四川: 电子科技大学, 2020.Xu Z Y. Research on point cloud registration in 3D reconstruction[D]. Sichuan: University of electronic science and technology, 2020(in Chinese with English abstract). [19] Li P, Wang R S, Wang Y X, et al. Fast method of registration for 3D RGB point cloud with improved four initial point pairs algorithm[J]. Sensors, 2020, 20(1): 1-25. doi: 10.1109/JSEN.2019.2959158 [20] Perumal L. New approaches for Delaunay triangulation and optimization[J]. Heliyon, 2019, 5(8): 1-18. http://www.sciencedirect.com/science/article/pii/S2405844019359791 [21] Kim J, Cho J. Delaunay triangulation-based spatial clustering technique for enhanced adjacent boundary detection and segmentation of LiDAR 3D point clouds[J]. Sensors, 2019, 19(18): 1-12. doi: 10.1109/JSEN.2019.2920795 [22] 孔德武. 点云数据的三角剖分及计算机三维重建[J]. 西南师范大学学报: 自然科学版, 2019, 44(7): 87-92. https://www.cnki.com.cn/Article/CJFDTOTAL-XNZK201907015.htmKong D W. Triangulation and computer three-dimensional reconstruction of point cloud data[J]. Journal of Southwest China Normal University(Natural Science Edition), 2019, 44(7): 87-92(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-XNZK201907015.htm [23] 张蓓蓓, 李国清, 冯梅, 等. 基于Delaunay三角剖分的多尺度POI提取技术研究与实现[J]. 测绘与空间地理信息, 2018, 41(6): 119-121, 125. doi: 10.3969/j.issn.1672-5867.2018.06.035Zhang B B, Li G Q, Feng M. Extraction technology research and implementation of multi-scale POI based on Delaunay triangulation[J]. Geomatics & Spatial Information Technology, 2018, 41(6): 119-121, 125(in Chinese with English abstract). doi: 10.3969/j.issn.1672-5867.2018.06.035 [24] 成思源, 杨雪荣. Geomagic studio逆向建模技术及应用[M]. 北京: 清华大学出版社, 2016.Cheng S Y, Yang X R. Reverse modeling technology and application of Geomagic studio[M]. Beijing: Tsinghua University Press, 2016(in Chinese). [25] Bringmann K, Künnemann M, Nusser A. Walking the dog fast in practice: Algorithm engineering of the Fréchet distance[J]. ArXiv, 2019, 17(1): 1-34. http://arxiv.org/abs/1901.01504 [26] Wylie T R, Zhu B H. Intermittent map matching with the discrete fréchet distance[J]. ArXiv, 2014, 1409(2456): 1-11. http://arxiv.org/abs/1409.2456 [27] Wylie T R. The discrete Fréchet distance and applications[D]. Bozeman Montana USA: Bozeman Montena State University, 2013. [28] 朱洁, 黄樟灿, 彭晓琳. 基于离散Fréchet距离的判别曲线相似性的算法[J]. 武汉大学学报: 理学版, 2009, 55(2): 227-232. doi: 10.3321/j.issn:1671-8836.2009.02.020Zhu J, Huang Z C, Peng X L. Curve similarity judgment based on the discrete fréchet distance[J]. Journal of Wuhan University (Natural Science Edition), 2009, 55(2)(in Chinese with English abstract). doi: 10.3321/j.issn:1671-8836.2009.02.020 [29] Mu Y S, Liu X D, Wang L D. A Pearson's correlation coefficient-based decision tree and its parallel implementation[J]. Information Sciences, 2017, 435: 40-58. http://smartsearch.nstl.gov.cn/paper_detail.html?id=afb17e37ca1fae5c9927ae93a6d209f8 -
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