Estimating underground mine ventilation friction factors from low density 3D data acquired by a moving LiDAR

作     者：Curtis Watson Joshua Marshall 

作者机构：Mining Systems Laboratory The Robert M.Buchan Department of Mining Queen's University 

基　　金：supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) under grant CRDPJ 44580412 Barrick Gold Corporation and Peck Tech Consulting Ltd 

出 版 物：《International Journal of Mining Science and Technology》 (矿业科学技术学报（英文版）)

年 卷 期：2018年第28卷第4期

页      码：650-655页

摘      要：Ventilation system analysis for underground mines has remained mostly unchanged since the Atkinson method was made popular by Mc Elroy in 1935. Data available to ventilation technicians and engineers is typically limited to the quantity of air moving through any given heading. Because computer-aided modelling, simulation, and ventilation system design tools have improved, it is now important to ensure that developed models have the most accurate information possible. This paper presents a new technique for estimating underground drift friction factors that works by processing 3 D point cloud data obtained by using a mobile Li DAR. Presented are field results that compare the proposed approach with previously published algorithms, as well as with manually acquired measurements.

主 题 词：Mine ventilation Mine design Mobile mapping Roughness estimation Friction factors LiDAR3D point clouds 

学科分类：0819[工学-海洋工程类] 081903[081903] 08[工学] 

核心收录：

D　O　I：10.1016/j.ijmst.2018.03.009

馆 藏 号：203300693...