Research On Estimation Of Coal Quality In Minefield And 3D Visualization Of Coal Seam Structure

With the rapid development of computer technology and the integration with traditional industries,informatization has become the development trend of coal mining enterprises,and digital mines have emerged at the historic moment.As part of this,three-dimensional visualization of coal seams in coal mines and estimation of coal quality indicators can effectively guide the production of coal mining enterprises.Based on the actual needs of coal mining enterprises,this paper analyzes the characteristics of mine fields,coal seams and related data information,studies three-dimensional modeling methods,coal seam elevation estimation models,and coal seam coal quality estim,ation models,and builds a plug-in-free,portable,cross-platform,and multiple Browser-compatible minefield coal quality estimation and 3D visualization model of coal seam structure.The specific research content is as follows:(1)Analyze the relationship and characteristics between borehole data,coal seam structure data and coal quality data generated in the process of coal mining and production,and design the data structure of the coal quality estimation and the 3D visualization model of coal seam structure,use Mysql database and Navicat database management tools to establish a database of coal seam sampling data in coal mines.(2)Aiming at the problem of sparse data points in the three-dimensional visualization of coal seams in coal mines,an elevation estimation model based on the Kriging algorithm in geostatistics was constructed to increase the drawing data points.In Kriging,the solution of the variogram determines the accuracy of its interpolation.Therefore,support vector regression(SVR)is used to fit the variogram to avoid the limitation and dependence on the selection of the variogram;it can be modified.The adaptive differential evolution algorithm(UMDE)of mutation direction solves the optimal parameters of SVR.The actual data of borehole and coal seam elevation in a coal mine are used for comparative experiments.The experimental results prove that the model in this paper has higher accuracy than the Kriging estimation model constructed by other optimization schemes.(3)In the production process of coal mining enterprises,predicting the coal quality information of the minefield is beneficial to the enterprises to guide production and sales and other links.A three-dimensional space coal quality indicator estimation model based on SVR-Kriging is constructed.Determine the spatial location of the data points according to the drilling coordinates and coal seam elevation data,construct the estimation model of the core indicators of coal quality,total moisture,ash,and calorific value,and use the actual coal mine data to compare the estimation accuracy of the model.The experimental results show that the coal quality index estimation model proposed in this paper has high estimation accuracy.(4)Combining object-oriented thinking,based on Spring-SpringMVC-MyBatis(SSM)development framework,Three.js three-dimensional engine,triangulation algorithm,using the coal seam elevation estimation model and coal seam coal quality index estimation model established in this paper,constructed a Web-based plug-in-free,portable,cross-platform,multi-browser-compatible three-dimensional visualization model of coal quality estimation and coal seam structure for wellfields,which intuitively displays the distribution range,spatial structure,and coal quality indicators of coal seams in wellfields,and It can be well integrated with the existing management software of coal enterprises to promote the informatization development of coal enterprises.