Prediction Model of Mining Subsidence with Probability Integration Method Based on Thickness Influences of Loose Layer
Abstract：In order to improve the predicted surface subsidence accuracy of the probability integration method under the mining in thick and loose layer, to show the slow convergence at the boundary of the subsidence basin, based on the theory of the probability integration method, a new prediction model was provided. The model had considered the influences of the loose layer thickness and a new parameter of the loose layer influence coefficient was introduced. In combination with a case verification of No. 1212 （3） coal mining face in Panbei Mine of Huainan Mining Area, the study results showed that the new prediction model would be higher predicted accuracy than the proba- bility integration model and the fitting relative error was decreased from 8% to 6%. The influence coefficient of the loose layer was posi- tively related to the main influence radius and the relationship between the coefficient and the radius was clear and the fitting effect was ex- cellent.
Keywords：loose layerprobability integration methodmining subsidenceprediction model
Publication Date：2012-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 10-12,16 )