Rock burst risk prediction method based on multi-factor pattern recognition and its application in coal mine

Rockburst is one of the typical dynamic disasters in coal mine, and risk prediction of rockburst is the primary task of implementing comprehensive prevention and control measures. In order to predict the risk of rockburst in different areas of No. 9 coal seam in Jixian coal mine, the geo-dynamic division method is adopted to determine the characteristics of fault developments and mine field structures. Geological structure model is established and the influencing factors of rockburst such as fracture structure, roof lithology, stress and mining depth are analyzed in this paper. On these basics, the multi-factor pattern recognition method for predicting rockburst risk is put forward, and the risk of rockburst in Jixian coal mine is divided into four grades. The prediction results of the comprehensive index method for the 4th panel in second mining area are compared with the prediction outcomes of the multi-factor pattern recognition method. Results show that the multi-factor pattern recognition method have good performance in predicting the rockburst risk, thus providing theoretical and technical support for the management of rockburst.