Whole basin modeling and parameter inversion of mining subsidence based on UAV photogrammetry technology

Taking Tangjiahui Mining Area in Inner Mongolia as the research object, the UAV photographic image data of August 2020 and March 2021 in this area were obtained, and DEM was produced. The subsidence basin in this area was obtained by subtracting the DEM data, and the denoising effects of different d...

Full description

Saved in:
Bibliographic Details
Published inMei kuang an quan Vol. 53; no. 2; pp. 179 - 186
Main Author LI Yuhao, AN Shikai, ZHOU Dawei, ZHAN Shaoqi, GAO Yingui
Format Journal Article
LanguageChinese
Published Editorial Office of Safety in Coal Mines 01.02.2022
Subjects
parameter inversion of the whole basin
point cloud denoise
robust analysis
simulated annealing algorithm
uav photogrammetry technology
Online AccessGet full text

Cover

More Information
Summary:Taking Tangjiahui Mining Area in Inner Mongolia as the research object, the UAV photographic image data of August 2020 and March 2021 in this area were obtained, and DEM was produced. The subsidence basin in this area was obtained by subtracting the DEM data, and the denoising effects of different denoising methods were compared with MATLAB software. Based on the subsidence data of the whole basin, the subsidence coefficient and the main influence tangent of the subsidence basin are obtained by using the probability integral parameter inversion with method of simulated annealing(SA). Using this parameter to simulate the subsidence basin, it is calculated that the measurement error is 589 mm, accounting for 8.1% of the maximum subsidence value. Finally, the robust analysis of the parameters is made, and when the error in the measurement accounts for (1% to 10%) the maximum subsidence value, the result of parameter calculation is reliable. The results show that the BP neural network algorithm can effectively re
ISSN:1003-496X
DOI:10.13347/j.cnki.mkaq.2022.02.028