关键词: 开采沉陷, 概率积分法, 开采沉陷预计系统, 最小二乘法, Matlab

Abstract: The prediction parameters of mining subsidence are calculated by the probability integral method of the surface deformation data obtained by the observation stations established on the surface of mining working face，and the mining subsidence of the surrounding area of mining working face or the mining working face under the similar mining conditions are predicted to conduct evaluation and guidance on the mining operation.Therefore，obtaining the prediction parameters of mining subsidence with high precision is the precondition of prediction and inversion of mining subsidence prediction.Based on Matlab software，the deformation data of observation points are fitted by the least square method to calculate the prediction parameters of mining subsidence with probability integral method.Combing with the drawing tools of Matlab software，the mining subsidence visualization system with the functions of data loading，coordinate transformation，calculation parameters，the output of calculation results，prediction and inversion of mining subsidence is developed.Taking the 11316 working face of Xieqiao coal mine，Huainan city as the research example，according to the deformation data of the observation points of the surface observation stations，the prediction parameters of mining subsidence are calculated，and comparison between predicted parameters and measured parameters is conducted.The results show that the predicted parameters calculated by the mining subsidence visualization system is consistent with the basic rules of the mining subsidence in Huainan & Huaibei mining area，and the inversion results of the mining subsidence visualization system is identical to the measured parameters.The mining subsidence visualization system can provide reference for realizing the prediction and inversion of mining subsidence with high precision.

Key words: Mining subsidence, Probability integral method, Mining subsidence prediction system, Least square method, Matlab