Extraction of rock pile block size in mining based on 3D laser point cloud

doi:10.13474/j.cnki.11-2246.2026.0123

Abstract

Abstract: Blast size is a key indicator for evaluating blast quality.Appropriate size not only enhances the efficiency of crushers but also significantly reduces energy consumption.This research utilizes the volume connected clustering segmentation(VCCS) algorithm and the local characteristic point cloud processing(LCCP) algorithm from the Point Cloud Library (PCL) to extract and analyze the block size in four classic blast pile areas of the Xiaozhashan limestone mine in Gansu province.The results show that as the block size of the ore increases,the accuracy of ore identification using the VCCS+LCCP algorithm significantly improves.Among the four blast piles,only the large block rate of pile 3 reached 14.59%,exceeding industry standards,thus necessitating secondary blasting or manual intervention to reduce its size.The large block rates of the other three piles were within a reasonable range,meeting the requirements for subsequent processing.In conclusion,this study confirms the effectiveness of three-dimensional laser point cloud technology in mining block size analysis,demonstrating its broad application prospects in enhancing the automation and accuracy of analysis.

Key words: VCCS algorithm, LCCP algorithm, mining blast size, image recognition, laser point cloud

CLC Number:

P237

HU Tianming, WANG Xingbang, HUANG Junyu, LI Kegong, WANG Haiyuan, LI Zhiming, LI Tao, ZHAO Weishan, NIAN Yanyun. Extraction of rock pile block size in mining based on 3D laser point cloud[J]. Bulletin of Surveying and Mapping, 2026, 0(1): 144-150.

References

[1] 严凡涛,刘英驰,李传伟,等.BPSM-Ⅲ型在线粒度分析仪在辽宁排山楼金矿的应用[J].中国矿业,2019,28(S2): 455-459.
[2] 武仁杰,李海波,于崇,等.基于统计分级判别的爆破块度预测模型[J].岩石力学与工程学报,2018,37(1): 141-147.
[3] 尤帆,耿向.筛分法和激光粒度法联合测定陆源碎屑岩粒度[J].计量学报,2021,42(3): 380-387.
[4] 吴开兴,朱平,张恋,等.江西龙南乡标稀土矿石干筛法和水洗筛分法颗粒粒度分析[J].中国稀土学报,2016,34(5): 632-640.
[5] CARLSSON O J,NYBERG L.A method for estimation of fragment size distribution with automatic image processing[C]//Proceedings of 1983 International Symposium on Rock Fragmentation by Blasting.[S.l.]:Luleå Tekniska Universitet,1983.
[6] ORD A.Real-time image analysis of size and shape distributions of rock fragments[J].AusIMM Bulletin and Proceedings,1989,294(1): 28-31.
[7] 蔡改贫,刘占,汪龙,等.基于形态学优化处理的标记符分水岭矿石图像分割[J].科学技术与工程,2020,20(23): 9497-9502.
[8] 曾凡智,黄子豪,周燕,等.基于改进分水岭-凹点分割的矿石粒径分级检测方法[J].计算机测量与控制,2023,31(8): 31-37.
[9] 王志忠,王永增,马连成,等.基于分水岭和形态学重构的矿石图像分割方法[J].物联网技术,2017,7(3): 89-91.
[10] LEIVA C,ACUÑA C,CASTILLO D.Development and validation of an online analyzer for particle size distribution in conveyor belts[J].Minerals,2021,11(6): 581.
[11] 王大坤,叶图强,闫大洋,等.基于三维激光扫描技术的爆破块度识别[J].有色金属工程,2022,12(11): 120-127.
[12] 涂文龙.基于点云凹凸性特征的露天铜矿爆堆块度计算方法[D].赣州: 江西理工大学,2022.
[13] LIU Qiang,SHI Fuqiang,WANG Xuguang,et al.Statistical estimation of blast fragmentation by applying 3D laser scanning to muck pile[J].Shock and Vibration,2022,2022(1): 3757561.
[14] WANG Yongzhi,TU Wenlong,LI Hui.Fragmentation calculation method for blast muck piles in open-pit copper mines based on three-dimensional laser point cloud data[J].International Journal of Applied Earth Observation and Geoinformation,2021,100: 102338.
[15] LIN Yangbin,WANG Cheng,ZHAI Dawei,et al.Toward better boundary preserved supervoxel segmentation for 3D point clouds[J].ISPRS Journal of Photogrammetry and Remote Sensing,2018,143: 39-47.
[16] ACHANTA R,SHAJI A,SMITH K,et al.SLIC superpixels compared to state-of-the-art superpixel methods[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2012,34(11): 2274-2282.
[17] FELZENSZWALB P F,HUTTENLOCHER D P.Efficient graph-based image segmentation[J].International Journal of Computer Vision,2004,59(2): 167-181.
[18] ALTMAN N S.An introduction to kernel and nearest-neighbor nonparametric regression[J].The American Statistician,1992,46(3): 175-185.
[19] STUTZ D,HERMANS A,LEIBE B.Superpixels: an evaluation of the state-of-the-art[J].Computer Vision and Image Understanding,2018,166: 1-27.
[20] KLASING K,ALTHOFF D,WOLLHERR D,et al.Comparison of surface normal estimation methods for range sensing applications[C]//Proceedings of 2009 IEEE International Conference on Robotics and Automation.Kobe: IEEE,2009: 3206-3211.
[21] MITRA N J,NGUYEN A.Estimating surface normals in noisy point cloud data[C]//Proceedings of the 9th Annual Symposium on Computational Geometry.San Diego: ACM Press,2003: 322-328.
[22] HOLZ D,SCHNABEL R,DROESCHEL D,et al.Towards semantic scene analysis with time-of-flight cameras[M]//RoboCup 2010: Robot Soccer World Cup XIV.Berlin,Heidelberg: Springer,2011: 121-132.
[23] RUSU R B.Semantic 3D object maps for everyday robot manipulation[M].Berlin,Heidelberg: Springer,2013.
[24] STEIN S C,SCHOELER M,PAPON J,et al.Object partitioning using local convexity[C]//Proceedings of 2014 IEEE Conference on Computer Vision and Pattern Recognition.Columbus: IEEE,2014: 304-311.
[25] 刘俊伟,陈晓青.基于计算机视觉的爆破块度分布统计[J].矿业研究与开发,2024,44(1): 190-196.
[26] PAPON J,ABRAMOV A,SCHOELER M,et al.Voxel cloud connectivity segmentation-supervoxels for point clouds[C]//Proceedings of 2013 IEEE Conference on Computer Vision and Pattern Recognition.Portland: IEEE,2013: 2027-2034.
[27] KAUFMAN A,SHIMONY E.3D scan-conversion algorithms for voxel-based graphics[C]//Proceedings of 1986 Workshop on Interactive 3D Graphics.[S.l.]:ACM Press,1987: 45-75.
[28] HANSEN C D,JOHNSON C R.Visualization handbook[M].[S.l.]:Academic Press,2005.
[29] 李辉.基于三维激光点云的爆堆块度分析[D].赣州: 江西理工大学,2020.
[30] MISHRA A K,NIGAM Y K,SINGH D R.Controlled blasting in a limestone mine using electronic detonators: a case study[J].Journal of the Geological Society of India,2017,89(1): 87-90.