Occurrence Characteristics And Coal Quality Variation Of Main Coal Seam In Zhungeer Huchaliang Coal Field

In this paper,the characteristics of the main coal mining area,the characteristics of coal quality and the change of coal quality analysis index are studied through the Zhungeer Huchaliang coal field,among which the correlation between the coal quality indexes of each main coal seam is diversified Linear regression model,the study provides the necessary theoretical guidance for coal mining,processing and utilization,and is conducive to the sustainable development of coal resources.Zhungeer Huchaliang coal field is located in the northeastern part of the Ordos station in North China.The topography of the terrain is the north-south direction.The coal-bearing strata are mainly the Lower Permian shanxi Formation and the Carboniferous Upper Taiyuan Formation.The No.6 upper No.6 and No.9 coal seams of the Upper Carboniferous Upper Taiyuan Formation are the main recoverable coal seams in this area.The thickness of No.6 upper coal seam is gradually thickened from northeast to southwest,and the thickness of No.6 coal seam is gradually thickened from east to west,and the thickness of No.9coal seam is gradually thinned from east to west.Based on the study of the change law of the coal quality index of the main coal seam,it is found that the ash content and volatiles of the No.6 upper,No.6 and No.9 coal seam are gradually decreasing from top to bottom for the vertical surface.The volatiles content of No.6 upper seam is increasing from northeast to southwest.The volatiles content of No.6 coal seam is decreasing from northeast to central,and the content of volatiles from the middle to the south is increasing.The volatiles content of No.9 coal seam is increasing from north to south.The ash content of No.6 coal seam and No.9 coal seam increased gradually from north to south,while the ash content of No.6 coal seam increased gradually from northwest to southeast.For the correlation between the coal quality indexes of each main coal seam,the multiple linear regression equation is used to analyze the multiple linear regression equation of calorific value and coal quality analysis index.Compared with BP neural network and support vector machine,it is found that the multiple linear regression model is better for predicting the unknown coal quality index in the coal seam.It is found that the error between the predicted value and the measured value of the model is within the allowable range,so the model can predict the unknown coal quality index in the coal seam,is conducive to the rational development of coal resources.