摘要
矿体三维建模是数字矿山的基础和核心.为了提高建模效率,减少人工干预,提出了基于偏差支持向量机(Biased-SVM)和Poisson曲面的矿体隐式自动三维建模方法.该方法通过对原始钻孔数据的学习建立最优分类函数,将离散化的建模空间内任意点分类为矿体外与矿体内;在此基础上提取矿体边界点,计算点云法向,建立表征矿体模型几何信息的有向点集;结合矿体点云模型采用Poisson曲面法建立矿体边界指示函数,并提取等值面形成矿体模型.针对不同矿体钻孔数据,采用该方法建立矿体模型,并与传统显式建模方法进行对比分析.结果表明:提出的方法具有人工干预少、自动化程度高、模型表达自然光滑等优点,为矿体的自动建模与更新提供了一条有效途径.
The 3D orebody modeling is the foundation and core technology of digital mine.In order to improve modelling efficiency and reduce artificial intervention,a new 3D orebody modeling method was proposed,which is based on Biased-SVM and Poisson surface.Firstly,the optimal classification prediction function was established through the study of original drilling data,and the arbitrary points in the discrete modeling space were classified as being either ore or non-ore.Secondly,the ore body boundary points were extracted on this basis,the normal vectors of the point cloud were calculated,and the oriented point set representing the geometric information of the orebody model was established.Thirdly,the Poisson surface method was used to establish the boundary function of the orebody,and the orebody model was established through extracting isosurface.The new method was applied to model the different orebodies,and compared with the traditional explicit modeling method.The results show that the newmethod have many advantages,such as less manual intervention,high degree of automation and the natural expression of model,which provides an effective way for automatic modeling and updating of orebodies.
作者
毕林
赵辉
李亚龙
BI Lin;ZHAO Hui;LI Yalong(School of Resources and Safety Engineering,Center of Digital Mine Research,Central South University,Changsha,Hunan 410083,China)
出处
《中国矿业大学学报》
EI
CAS
CSCD
北大核心
2018年第5期1123-1130,共8页
Journal of China University of Mining & Technology
基金
国家自然科学基金项目(41572317)
国家高技术研究发展计划(863)项目(2011AA060402)
中央高校基本科研业务费专项资金项目(2017zzts790)
