Abstract:

Based on the distance discriminant analysis model of rockburst prediction, and combined the characteristics and the principle of Bayes discriminant analysis theory, a Bayes discriminant analysis method to predict rockburst in underground engineering is presented. Some main control factors of rockburst, such as the values of in-situ stresses , the compressive strength and tensile strength of rock, the elastic energy index of rock , are selected as the discriminant factors of the Bayes discriminant analysis model; and the resubstitution method is used to estimate the ratio of mistake-distinguish. The data of a series of underground rock projects at home and abroad are taken as the training and testing samples. Rockburst of three tunnels are used to verify this model. The results show that the Bayes discriminant analysis model of rockburst has excellent performance and high prediction accuracy.

Key words: underground engineering, rockburst, Bayes discriminant analysis, distance discriminant analysis, tunnel, mine