粒子群投影寻踪算法在岩爆预测中的应用  

Application of Projection Pursuit Model and Particle Swarm Optimization in Rock Burst Prediction

作　　者：周宣赤[1] 白春华[1] 王仲琦[1] 林大超[2] 

机构地区：[1]北京理工大学爆炸科学与技术国家重点实验室,北京100081 [2]华北科技学院建筑学院,北京101601

出　　处：《上海交通大学学报》2012年第12期1956-1961,1966,共7页Journal of Shanghai Jiaotong University

基　　金：爆炸科学与技术国家重点实验室基金资助项目(ZDKT08-2-6;YBKT09-1)

摘　　要：对岩爆有影响的三项主要因子:洞室最大切向应力与岩石单轴抗压强度的比值、脆性系数和弹性能量指数作为岩爆灾害预测的主要判别指标,通过粒子群优化算法和投影寻踪算法建立了相应的岩爆预测分析模型.该模型采用粒子群算法优化投影指标函数,确保了模型参数的准确性;同时利用逻辑斯谛曲线函数建立投影值与经验等级之间的非线性关系.研究表明,用粒子群投影寻踪回归模型进行岩爆预测,避免了传统预测方法由于主观原因造成的误差,预测精度较高.通过将所建模型应用到秦岭隧道和冬瓜山铜矿的岩爆预测中,得到与实际情况较符合的预测结果.In order to construct the measure of rock burst intensity,the ratio of maximum tangential stress of cave chamber to uniaxial compressive strength of rock,brittleness coefficient and elastic energy index are chosen as the discriminant index,an appropriate analysis model for rock burst prediction was established based on particle swarm optimization and projection pursuit algorithm.Firstly,for the sake of ensuring the accuracy of the model parameters,particle swarm optimization is used to optimize the projection index function,meanwhile the non-linear relationship between projected value and empirical value is obtained by use of logistic curve function.The study shows that the prediction of rock burst intensity with use of the regression model based on particle swarm and projection pursuit has the advantage over traditional forecasting methods in that the deviation caused by subjective reasons can be avoided and its prediction precision is high.Finally,the model was applied to the rock burst prediction of Qinling tunnel and Dongguashan copper ore and the result corresponds with actual situation which shows scientificity,feasibility and effectiveness of the model in rock burst prediction.

关 键 词：投影寻踪 粒子群优化 地下洞室 岩爆预测 

分 类 号：TD853[矿业工程—金属矿开采]