摘要
三维激光扫描技术具有高效率、高精度、低成本等优点,能够实现复杂矿井三维模型的快速构建。然而,该技术存在获取的点云数据体量庞大、噪声大等不足,给数据存储、传输、处理带来诸多不便。为解决上述问题,提出了巷道三维激光扫描点云复合滤波算法。依据算法侧重点和点云特征将数据滤波划分为精简与降噪两个过程,进而结合矿山半圆拱巷道特征提出了“剖面—轴向—随机”复合式数据精简滤波模型和复合式数据降噪滤波模型,并对复合算法的适用性、可靠性、合理性、准确性进行了对比分析。结果表明:相比单一算法,采用复合滤波算法精简与降噪后,在合理保留巷道原有的轮廓特征与细节的同时,数据简化率高达99.3%,最大程度滤除了椒盐噪声、高斯噪声等各类离群点,实现了确保模型质量前提下数据大规模精简与离群点高效处理的目标,为矿山全生命周期实时状态展示、动态评估、行为预测奠定了基础。
3D laser scanning technology has the advantages of high efficiency,high precision and low cost,and can real-ize the rapid construction of complex mine 3D model.However,this technology has some problems such as large volume of point cloud data and large noise,which brings a lot of inconvenience to data storage,transmission and processing.To solve the above problems,a three-dimensional laser scanning point cloud composite filtering algorithm for roadway is proposed.In this paper,data filtering is divided into two processes:reduction and noise reduction according to the algorithm focus and point cloud characteristics,and then combined with the characteristics of mine semicircular arch roadway,a"profile-axial-random"composite data reduction filtering model and a composite data noise reduction filtering mathematical model are proposed,and the applicability,reliability,rationality and accuracy of the composite algorithm are compared and analyzed.The test results show that compared with the single algorithm,after using the composite filter algorithm to simplify and reduce noise,the original contour features and details of the roadway are reasonably preserved,the data simplification rate is as high as 99.3%,and all kinds of outliers such as pepper and salt noise and Gaussian noise are filtered out to the maximum extent.It achieves the goal of large-scale data simplification and efficient processing of outlier points under the premise of ensuring model quality,and lays a foundation for real-time state display,dynamic evaluation and behavior prediction of mine whole life cycle.
作者
李龙龙
宫成
李雨成
崔豫楠
毋晓军
李玉良
LI Longlong;GONG Cheng;LI Yucheng;CUI Yunan;WU Xiaojun;LI Yuliang(College of Safety and Emergency Management Engineering,Taiyuan University of Technology,Taiyuan 030024,China;Shaanxi Coal Group Shennan Industry Development Co.,Ltd.,Shenmu 719300,China)
出处
《金属矿山》
CAS
北大核心
2023年第11期205-212,共8页
Metal Mine
基金
山西省基础研究计划(自由探索类)青年科学研究项目(编号:202203021222132,202203021212218)。
关键词
三维激光扫描
半圆拱巷道
数据滤波
点云数据
矿山智能化
3D laser scanning
semicircular arch roadway
data filtering
point cloud data
mine intelligence