基于三维激光点云的矿山矿石爆堆块度提取

doi:10.13474/j.cnki.11-2246.2026.0123

测绘通报 ›› 2026, Vol. 0 ›› Issue (1): 144-150.doi: 10.13474/j.cnki.11-2246.2026.0123

基于三维激光点云的矿山矿石爆堆块度提取

胡天明^1,2, 王兴邦^3,4, 黄俊瑜³, 李克恭^1,2, 王海员³, 李治明^1,2, 李涛^1,2, 赵伟山^1,2, 年雁云³

1. 甘肃省测绘工程院, 甘肃兰州 730000;
2. 甘肃省应急测绘工程研究中心, 甘肃兰州 730000;
3. 兰州大学资源与环境学院, 甘肃兰州 730000;
4. 甘肃省地矿局第三地质矿产勘查院, 甘肃兰州 730050

收稿日期:2025-05-12 发布日期:2026-02-03
通讯作者: 年雁云。E-mail:yynian@lzu.edu.cn
作者简介:胡天明(1985—),男,高级工程师,主要从事遥感测绘地理信息。E-mail:562059651@qq.com
基金资助:
甘肃省科技厅联合基金重点项目(24JRRA802);甘肃省科技计划(22YF7FA074)

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

HU Tianming^1,2, WANG Xingbang^3,4, HUANG Junyu³, LI Kegong^1,2, WANG Haiyuan³, LI Zhiming^1,2, LI Tao^1,2, ZHAO Weishan^1,2, NIAN Yanyun³

1. Gansu Provincial Surveying and Mapping Engineering Institute, Lanzhou 730000, China;
2. Gansu Provincial Emergency Surveying and Mapping Engineering Research Center, Lanzhou 730000, China;
3. College of Resources and Environment, Lanzhou University, Lanzhou 730000, China;
4. Third Geological and Mineral Exploration Institute of Gansu Provincial Bureau of Geology and Mineral Resources, Lanzhou 730050, China

Received:2025-05-12 Published:2026-02-03

摘要/Abstract

摘要： 爆破块度是评价爆破质量的关键指标,合适的块度不仅可以提升破碎机的工作效率,还能显著降低能耗。本文采用点云库PCL中的体积连通性聚类分割(VCCS)算法和局部特征点云处理(LCCP)算法,对甘肃省小喳山石灰岩矿的4个经典爆堆区域进行块度提取和分割分析。研究结果显示,随着爆堆矿石块度的增大,VCCS+LCCP算法在矿石识别上的正确率也显著提高。在4个爆堆中,仅3号爆堆的大块率达到14.59%,超出了行业标准范围,因此需要进行二次爆破或人工干预以降低其块度;而其他3个爆堆的矿石大块率均在合理范围内,符合后续处理的要求。综上所述,本文方法证实了三维激光点云技术在矿山块度分析中的有效性,显示了其在提升分析的自动化水平与精确度方面的广阔应用前景。

关键词: VCCS算法, LCCP算法, 矿山爆破块度, 图像识别, 激光点云

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

中图分类号:

P237

胡天明, 王兴邦, 黄俊瑜, 李克恭, 王海员, 李治明, 李涛, 赵伟山, 年雁云. 基于三维激光点云的矿山矿石爆堆块度提取[J]. 测绘通报, 2026, 0(1): 144-150.

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.

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基于三维激光点云的矿山矿石爆堆块度提取

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

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