Three-dimensional Visualization Research On Coal Seam Structure And Coal Quality Prediction In Fully Mechanized Mining Face

With the rapid development of computer technology,the tide of social information has swept the world,the computer has become an indispensable auxiliary tool for people to deal with work.Computer technology is also widely used in the coal industry.Based on the actual demand of coal quality management in coal enterprises,this paper explores the prediction model of coal seam structure and core index of coal quality in fully mechanized coal face,and directly expresses the prediction process and results in the form of three-dimensional visualization.Specific research contents are as follows:(1)In view of the problem that the variation function model selected and fitted by the traditional Kriging interpolation algorithm cannot better reflect the actual geological space variation trend,the interpolation prediction model of coal seam structure in fully mechanized mining face based on UPso-Kriging method is proposed:Firstly,the USPO algorithm is proposed to solve the problems of the original PSO algorithm,such as slow convergence speed and easy to fall into local solution.Then,the UPSO algorithm was introduced into Kriging interpolation to solve the parameters of the variation model,and the fitting of the variation function model was completed.The elevation interpolation prediction model of the coal seam structure in fully mechanized mining face was built based on UPso-Kriging method,and the elevation interpolation estimation was carried out based on the actual data of the fully mechanized mining face already mined by a coal enterprise.The experimental results were compared with the original Kriging interpolation method and PSO-Kriging interpolation algorithm.The results show that compared with other methods,the estimation accuracy of the elevation obtained by UPSO-Kriging method is higher,and it can describe the actual geological conditions more accurately.Finally,the DEM spatial data model is established based on the regular grid method by analyzing the characteristics of the interpolation data,which lays a theoretical foundation for the three-dimensional visualization of coal seam structure in working face.(2)In view of the problem that the calculation of gangue volume in the predicted area depends on manual estimation with large error in the process of core index estimation of coal quality by empirical formula in a coal enterprise,the idea of grid method for irregular ore body volume calculation is firstly proposed.Then,Monte Carlo method was introduced to further optimize the calculation of the irregular orebody volume,aiming at the problem of poor accuracy of grid area in the calculation of irregular body by the original method.Finally,the estimation model of coal quality core index of fully mechanized coal face based on Monte Carlo optimization grid(MC-Gird)method was established,and the comparison test was conducted with the actual data of the working face.The results show that the index data estimated by the Monte Carlo Optimized Grid Grid(MC-GIRD)method proposed in this paper is closer to the actual sampling data when applied to the prediction model of coal core index.(3)On the basis of the above theoretical research results,aiming at the poor portability of the existing 3D visualization software and the situation that coal enterprises have many production departments and far subunits,the four-layer architecture design mode based on SpringBoot+ SSM framework is designed.The coal quality prediction and 3D visualization system of fully mechanized mining face with simple operation and complete separation of control layer and business logic layer is designed.The basic functions of related data management,geological graph drawing and display,coal quality prediction and report output are realized,which further verifies the feasibility and application value of the research results in this paper.