Six main influencing factors： slope, aspect, distance, angle, angle of coal seam, and the ratio of depth and thickness, were selected by Grey correlation theory and Grey relational analysis procedure programmed by th...Six main influencing factors： slope, aspect, distance, angle, angle of coal seam, and the ratio of depth and thickness, were selected by Grey correlation theory and Grey relational analysis procedure programmed by the MATLAB software package to select the surface movement and deformation parameters. On this basis, the paper built a BP neural network model that takes the six main influencing factors as input data and corresponding value of ground subsidence as output data. Ground subsidence of the 3406 mining face in Haoyu Coal was predicted by the trained BP neural network. By comparing the prediction and the practices, the research shows that it is feasible to use the 13P neural network to predict mountain mining subsidence.展开更多
Attempted to conduct a dynamic monitoring research on coal mining subsidence in western mining areas by using the method of combining D-InSAR and GPS technology. The observation points were installed on the main secti...Attempted to conduct a dynamic monitoring research on coal mining subsidence in western mining areas by using the method of combining D-InSAR and GPS technology. The observation points were installed on the main section and the three-dimensional coordinates of the points were measured by using the method of dynamic differential GPS. Meanwhile, the radar images of this subsidence area were processed by using the method of interferometry with daris software, and the interferogram of the subsidence area was obtained. Through this study, the GPS monitoring data and the InSAR deformation data were integrated and the dynamic subsidence contours of the experimental area were obtained. GPS/InSAR fusion technology provides a new technological means for large-scale dynamic monitoring of coal mining subsidence in western mountainous mining areas and shows good application prospects in coal mining subsidence monitoring and disaster warning.展开更多
In order to study the law of mining subsidence and ground movement, to provide the basis of coal mining under building, railway and water, we used the probability integration method to make comprehensive evaluation of...In order to study the law of mining subsidence and ground movement, to provide the basis of coal mining under building, railway and water, we used the probability integration method to make comprehensive evaluation of ground stability. Take Yingcheng Coal Mine of Jiutai as an example. Mining-induced movement and horizontal movement are analyzed on the basis of the measurement data. The resuhs of prediction can pro- vide reference and basis for prevention of coal mining subsidence and future restoration and treatment.展开更多
文摘Six main influencing factors： slope, aspect, distance, angle, angle of coal seam, and the ratio of depth and thickness, were selected by Grey correlation theory and Grey relational analysis procedure programmed by the MATLAB software package to select the surface movement and deformation parameters. On this basis, the paper built a BP neural network model that takes the six main influencing factors as input data and corresponding value of ground subsidence as output data. Ground subsidence of the 3406 mining face in Haoyu Coal was predicted by the trained BP neural network. By comparing the prediction and the practices, the research shows that it is feasible to use the 13P neural network to predict mountain mining subsidence.
基金Supported by the Natural Science Foundation of Shannxi Province
文摘Attempted to conduct a dynamic monitoring research on coal mining subsidence in western mining areas by using the method of combining D-InSAR and GPS technology. The observation points were installed on the main section and the three-dimensional coordinates of the points were measured by using the method of dynamic differential GPS. Meanwhile, the radar images of this subsidence area were processed by using the method of interferometry with daris software, and the interferogram of the subsidence area was obtained. Through this study, the GPS monitoring data and the InSAR deformation data were integrated and the dynamic subsidence contours of the experimental area were obtained. GPS/InSAR fusion technology provides a new technological means for large-scale dynamic monitoring of coal mining subsidence in western mountainous mining areas and shows good application prospects in coal mining subsidence monitoring and disaster warning.
文摘In order to study the law of mining subsidence and ground movement, to provide the basis of coal mining under building, railway and water, we used the probability integration method to make comprehensive evaluation of ground stability. Take Yingcheng Coal Mine of Jiutai as an example. Mining-induced movement and horizontal movement are analyzed on the basis of the measurement data. The resuhs of prediction can pro- vide reference and basis for prevention of coal mining subsidence and future restoration and treatment.
