Study on prediction method of coal seam gas content based on principal component multiple regression

Abstract

The gas content of coal seam is the basis of gas disaster control in coal mine. The accurate prediction of gas content of coal seam is directly related to the effect of gas precise control in coal mine. Weijiadi coal mine is a high gas mine in Gansu Province, the gas content of NO.1 coal seam is related to five factors, including burial depth, elevation of coal seam floor, vertical depth, thickness of coal seam and total thickness of coal seam. In order to avoid the problem that only one factor is taken into account in the statistical analysis and study of coal seam gas occurrence law and the one-dimensional linear model is not accurate in prediction, this paper determines the gas content of NO.1 coal seam through principal component analysis, the thickness and buried depth of coal seam are the main control factors of gas content in coal seam. The predicted value of gas content in coal seam is obtained by multiple linear regression analysis, and compared with the measured value, the predicted value is basically consistent with the measured value, which is of great significance for the prevention and control of gas disaster in coal mine.