Orebody Modeling Method Based on the Normal Estimation of Cross-Contour Polylines

Zhaohao Wu, Deyun Zhong, Zhaopeng Li, Liguan Wang and Lin Bi
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Zhaohao Wu: School of Resources and Safety Engineering, Central South University, Changsha 410083, China
Deyun Zhong: School of Resources and Safety Engineering, Central South University, Changsha 410083, China
Zhaopeng Li: School of Resources and Safety Engineering, Central South University, Changsha 410083, China
Liguan Wang: School of Resources and Safety Engineering, Central South University, Changsha 410083, China
Lin Bi: School of Resources and Safety Engineering, Central South University, Changsha 410083, China

Mathematics, 2022, vol. 10, issue 3, 1-15

Abstract: The normal estimation of cross-contour polylines largely determines the implicit orebody modeling result. However, traditional methods cannot estimate normals effectively due to the complex topological adjacency relationship of the cross-contour polylines manually interpreted in the process of exploration and production. In this work, we present an orebody implicit modeling method based on the normal estimation of cross-contour polylines. The improved method consists of three stages: (1) estimating the normals of cross-contour polylines by using the least square plane fitting method based on principal component analysis; (2) reorienting the normal directions by using the method based on the normal propagation; (3) using an implicit function to construct an orebody model. The innovation of this method is that it can automatically estimate the normals of the cross-contour polylines and reorient normal directions without manual intervention. Experimental results show that the proposed method has the advantages of a small amount of calculation, high efficiency and strong reliability. Moreover, this normal estimation method is useful to improve the automation of implicit orebody modeling.

Keywords: implicit modeling; radial basis function; principal component analysis; normal propagation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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