Research on the spatiotemporal prediction of mining deformation with subcritical extraction integrated with D-InSAR technology

Abstract

The prediction of surface movement and deformation in the mining area is of great significance to the production of the mining. Since the differential interferometry synthetic aperture radar measurement (D-InSAR) technology cannot predict the deformation caused by mining face, and the existing probability integral method (PIM) prediction model can only predict final mining deformation under critical extraction. Therefore, on the basis of PIM prediction model, the simplified Boltzmann function and Gompertz time function were introduced to form the BPIM dynamic prediction model for the analysis of temporal and spatial characteristics of the mining area. The parameters of BPIM model are inversed by D-InSAR monitoring data combined with optimization algorithm, and the mining of the working face is followed by the dynamic forward prediction of the changes in temporal and spatial characteristics. In addition, we analyzed the sensitivity of the main parameters in the model to the predicted results and the variation relationship of the model subsidence coefficient with the mining of the working face. When the model was applied to the working face of Guobei coal mine, the RMSE of the BPIM dynamic prediction model is 25.1 mm. Constructed with the previous dynamic prediction model established by conventional methods, its deformation accuracy under the prediction of subcritical extraction on the surface of the mining area is improved by 58.7%. The results demonstrated that the BPIM dynamic model effectively avoids the problem of large prediction results under subcritical extraction, and can provide some suggestions for the planning and production of the mining area.