GAO K Y, DU W B,CHEN J H, et al. Application research of OT technology combined with UAV LiDAR in surface subsidence monitoring in mining area[J]. Journal of Henan Polytechnic University(Natural Science) , 2025, 44(1): 80-87.

doi: 10.16186/j.cnki.1673-9787.2023110010

Received: 2023/11/07

Revised: 2024/02/04

Published: 2025/01/02

Application research of OT technology combined with UAV LiDAR in surface subsidence monitoring in mining area

GAO Kuiying1, DU Weibing2,CHEN Jianhua1, YANG Bin1,ZHANG Hebing2,XU Zhao1, FENG Zhizhong1, ZHANG Wenzhi2

1. Daliuta Coal Mine， China Energy Shengdong Coal Group Co.， Ltd.， Shenmu 719315， Shaanxi， China; 2. School of Surveying and Land Information Engineering， Henan Polytechnic University， Jiaozuo  454000， Henan， China

Abstract: Objectives In order to give full play to the application value of remote sensing monitoring at different scale in identifying surface deformation of high-intensity coal mining， Methods satellite image offset tracking and UAV LiDAR （Light Detection and Ranging） technology are used to obtain two typical subsidence areas and their parameters of the working face scale. The differences of these two remote sensing monitoring methods between these two different scales are demonstrated by combining the ground observation station data. Results Taking the two-scene SAR images of Shendong mining area as an example， during the research period， the mining area was mostly located in the center of surface subsidence， with subsidence values ranging from -3.8 to 0 m by using the offset tracking technology. The UAV LiDAR technology can effectively identify the subsidence range and magnitude on the scale of the working face. The surface subsidence in the secondary and tertiary mining areas was higher than that in the primary mining areas， and the subsidence in the areas with underground coal pillars was relatively small， ranging from -1.17~0 m. Comparing and analyzing the difference between the differential data of unmanned aerial UAV LiDAR and satellite offset tracking results in two typical areas of the working face， the accuracy of the latter was higher in areas with smaller subsidence， while the accuracy of former was higher in areas with larger subsidence. The two subsidence coefficients obtained were 0.61 and 0.7,respectively， indicating that the subsidence coefficient obtained by UAV LiDAR was closer to the measured subsidence coefficient on the ground. The subsidence coefficient obtained by the UAV LiDAR is closer to the subsidence coefficient measured on the ground. Conclusions This research results could provide reference for large-scale and efficient mining subsidence monitoring.

Key words: high-intensity coal mining; offset tracking; UAV LiDAR; mining subsidence