Study On Coal Quality Prediction Of Ningdong Gasification Coal In Coal Chemical Industry

Coal gasification is the core of the coal chemical industry, and the coal quality directly affects the properties of coal gasification efficiency and the quality of syngas, stable operation of the gasification stove. For the long term strategic thinking, in order to providing stable and reliable gasification raw coal for Ningdong coal chemical industry, it is necessary to carry out prediction research for Ningdong coal mining area and its change rule. This paper used Kriging interpolation method to prediction the quality and distribution of Ningdong coal mining. By using multiple linear regression and RBF neural network, it forecast the change rule of the mining working face coal quality; to the need of Ningdong four kinds of gasifier for coal quality, it is established the coal quality evaluation system in coal chemical industry. The research results are as follows:Based on the analysis of the coal quality data of MeiHuajing mine of Ningdong area, using geostatistics module in GS+9.0 software, obtained the variation function of 4#,6#,10# coal quality seam(Mad, Aad, Vdaf, St,d, Qnet,ar, FT), according to the model of variation function, by Kriging interpolation method, predicted the coal quality and its distribution law of three main coal seams in MeiHuajing mine.The results show that, from top to bottom of the three main mining coal seams, Mad slightly decreases trend, most of the coal Mad content is 6~10%, mainly for medium and low water coal; Aad small changes, the Aad of the mining coal seam is 6.00~22.00%, most of the region is the ultra low ash, and low ash coal, for the partial is medium coal ash; Vdaf changes little, the Vdaf of the mining coal seam is 31.57~35.50%, which belongs to medium and high volatile coal; St,d has a trend of decrease, the St,d of the mining coal seam is 0.28~1.57%, on the horizontal direction, most of this area is low and ultra low sulfur coal, mainly is low sulfur coal; Qnet,ar with little change, the Qnet,ar of the mining coal seam is 25.56~27.86 MJ/kg, on the horizontal direction, most of the area is high calorific value coal, partial is medium calorific value; FT changes little, the FT of the mining coal seam is 1183~1385 ?, FT of the three coal seam are gradually increased from west to east, the western region is dominated by low FT and the east is middle FT.The coal quality prediction of the working face is based on the data of 90 sets of monthly working face of the 6 coal seam from 2010 to 2014 of Mei Huajing mine, the change of ash content was predicted by the method of multiple linear regression and radial basis function neural network prediction. The results show that:the coal ash content can be used multiple linear regression prediction model representation: Y=- 0.5239 + 0.552X1- 0.199X2+0.960X3(Y:pre ash, X1: pre ash of coal seam, X2:last month ash, X3:last month ash of coal seam). The result of multiple linear regression prediction is sensitive to the extreme points, easy to fall into local minimum. RBF neural network forecasting the monthly quality of the results of the error is smaller, more consistent with the actual situation. Ash prediction model tend to be more nonlinear results.According to the requirement of the Ningdong coal chemical industry base four gasifier of coal quality, combined with the coal quality prediction results, established a coal quality evaluation system for coal gasification in Ningdong coal gasification, the system can predict the future coal source of coal gasification for Ningdong coal chemical base.