采矿与安全工程学报2025，Vol.42Issue(5)：1153-1163,11.DOI:10.13545/j.cnki.jmse.2025.0039
露天煤矿边坡形态参数无人机识别及安全评价
Drone-based identification and safety evaluation of slope morphology parameters in open-pit coal mines
摘要
Abstract
The precise identification and comprehensive safety evaluation of slope morphology parame-ters are critical to ensuring safe production in open-pit coal mines.Traditional manual inspection and sin-gle-point measurement methods are inefficient,offer limited coverage,and struggle to achieve quantita-tive verification of over-limit slope morphology parameters and integrated safety evaluation.To address these issues,this study proposed an automated method for extracting slope morphological parameters and evaluating slope safety based on drone-derived 3D point cloud data in open-pit coal mines.By taking 51 open-pit coal mines at the border of Inner Mongolia Autonomous Region and Shaanxi Province as the re-search object,the following research work was conducted:First,high-precision 3D point cloud data were acquired with the aid of LiDAR-equipped drones.Based on these data,slope segmentation,top/bottom line extraction,and grid-based calculation of key parameters,including step height,platform width,bench slope angle,and overall slope angle,were achieved through slope threshold classification,morphological skeletonization,and local curve fitting.With reference to national mine safety standards,a slope morphology safety index(SMSI)was established to quantify the risk levels and weights of four over-limit factors(bench height,platform width,bench slope angle,and overall slope angle).The re-sults indicate that serious over-limit risks related to slope morphology are identified in the majority of the 51 open-pit coal mines,with frequent occurrences of overall slope angle overstepping and severe plat-form width insufficiency.Mining Cluster 1 shows the highest average(12.05)and standard deviation(9.31)of SMSI,which reflects the most severe and heterogeneous slope safety issues.Small-sized pri-vately owned mines in the study area are particularly prone to over-limit risks related to slope morpholo-gy,necessitating prioritized regulatory intervention.The proposed method,which significantly improves the efficiency of parameter extraction and reduces manual verification costs,are expected to provide pre-cise risk classification and regulatory prioritization for mine enterprises and supervisory authorities.关键词
露天煤矿/边坡形态参数/安全评价Key words
open-pit coal mines/slope morphology parameters/safety evaluation分类
矿业与冶金引用本文复制引用
田雨,王知乐,徐俣璠,计楚柠,雷少刚,周伟,陆翔,宫传刚..露天煤矿边坡形态参数无人机识别及安全评价[J].采矿与安全工程学报,2025,42(5):1153-1163,11.基金项目
国家自然科学基金项目(52304157,52204182) （52304157,52204182）
江苏省卓越博士后计划项目(2023ZB112) （2023ZB112）
国家重点研发计划项目(2023YF1306005) （2023YF1306005）
