【作者】 宫凤强； 李夕兵； 张伟；

【Author】 GONG Fengqiang~(1,2),LI Xibing~1,ZHANG Wei~(1,3) (1.School of Resources and Safety Engineering,Central South University,Changsha,Hunan 410083,China; 2.Rock Mechanics Laboratory,Swiss Federal Institute of Technology Lausanne(EPFL),Lausanne CH - 1015,Switzerland; 3.Changsha Engineering and Research Institute of Nonferrous Metallurgy,Changsha,Hunan 410011,China)

【机构】 中南大学资源与安全工程学院； 瑞士洛桑联邦理工大学岩石力学实验室； 长沙有色冶金设计研究院；

【摘要】 在岩爆发生和烈度分级预测的距离判别分析模型的基础上,结合地下工程岩爆的特点和Bayes判别分析理论,提出了地下工程岩爆发生及烈度分级预测的Bayes判别分析方法。综合分析影响岩爆主要因素,选取最大切向应力σ_θ、岩石抗压强度σ_c、岩石抗拉强度σ_t和弹性能量指数W_et作为影响岩爆的判别指标,并把σ_θ/σ_c、σ_c/σ_t和W_et作为判别因子建立岩爆预测的Bayes判别分析模型,利用国内外一些重大深部地下工程实例作为学习的样本进行训练。经过训练后的模型回判估计的误判率为零。利用该模型对国内典型的隧道和矿山岩爆情况进行预测,结果与实际情况符合得很好,说明该模型在岩爆发生可能性及烈度分级预测中具有良好的适用性和有效性。更多还原

【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 engineerings was presented in this paper.Some main control factors of rockburst, such as the values of in-situ stressesσ_θ.the compressiveσ_c and tensile strengthensσ_t,of rock,the elastic energy index of rock W_et>were selected in the analysis.Three factor indexes including the ratio ofσ_θ/σ_c andσ_c /σ₁、and W_et were regarded as discriminant factor of the Bayes discriminant analysis model and a series of underground rock projects at home and abroad were taken as the training and testing samples.Rockburst of several tunnels and mines were used to verify this model.The results show that the Bayes discriminant analysis model of rockburst has excellent performance and the prediction accuracy is very high.更多还原