基于BP神经网络的高含水岩石爆破震动参数预报  

Forecast of Blasting Vibration Parameters in High Water Cut Rock based on BP Neural Network

作　　者：李玉能[1,2] 马建军[1] 池恩安 陈永麟 

机构地区：[1]武汉科技大学理学院,武汉430081 [2]贵州新联爆破工程集团有限公司,贵阳550000

出　　处：《爆破》2017年第2期68-73,共6页Blasting

基　　金：基金项目:黔科合支撑[2016]2312

摘　　要：运用现场试验震动监测得出水介质对高含水岩石爆破地震波传播规律的影响,再结合BP神经网络理论,将水介质纳入网络模型,建立爆破震动参数预报的BP神经网络模型。采用高含水岩石爆破现场监测数据对网络模型进行训练。把训练达到最优后的预报结果与实测结果作对比,发现BP神经网络模型预报参数与实测值较为接近。The influence of water medium on the propagation law of blasting vibration in high water cut rock is studied by vibration monitoring in field test. Combining with the BP neural network theory, the water medium is incor- porated into the network model to establish the blasting vibration parameter forecasting model. The network model is trained by using site monitoring data of high water cut rock blasting. The optimum results of BP neural network model after training are compared with the measured data. It is found that the BP neural network model is close to the measured value, which is instructive for such engineering blasting.

关 键 词：高含水岩石 BP神经网络 爆破震动 预报模型 

分 类 号：TD235[矿业工程—矿井建设]