Analysis Of Distribution Law Of Surface Subsidence Based On Network Observation Stations

Coal resources is still one of Chinese major energy sources,and the coal-based energy pattern will not change in a short period of time.The demand for coal resources is increasing dramatically as the industrialization and urbanization grow rapidly.As the problem of coal resources under the building has become an important problem,the damage mining caused by the mining of coal resources under the building is getting more and more serious.To solve the problem mentioned above,it is urgent to study the prediction of ground movement,this paper conduct research on the distribution of surface subsidence at any point,which is of great significance for the safety mining of coal under the building.In this paper,we introduced the prediction modeling of Knothe influence Method,stochastic medium theory,probability integral method respectively.The influence function of all prediction modeling are Normal distribution First of all,we analyze the historical data monitored by the mesh observation station,to test and verify whether the distributions of surface subsidence of observation lines meet the the normal distribution.Followed by,based on the principle of mathematical statistics,the SPSS(Statistical Product and Service Solutions,SPSS)software is used to do statistical Analysis.It is shown that distribution of surface subsidence of observation lines meets the the normal distribution roughly.These include the lines of strike cross section,inclined cross section and lines of paralleling to the main section,except for the 103-F1 observation lines which is the farthest line from the inclined cross section.Finally,we combining the method of probability integral,based on the predicted formula of surface subsidence at any point,the degree of surface subsidence of the observation lines which are paralleled to the cross section in the mesh observation station is predicted and compared with the measured results.It is concluded that the predicted average relative error of the cross section in above formula is the smallest,and while the direction of cross section deviates further,the average relative error of the other observation lines parallel to the main section is gradually increased.The research results revise the prediction modeling and parameter,which is practical to improve the prediction reliability.