邻近隧道爆破震速预测及控制方法研究

Study on Prediction and Control Method of Peak Particle Vibration Velocit on Nearby Existing Tunnel

针对某隧道改扩建项目中,新建隧道爆破开挖可能对邻近老隧道的服役性能造成影响的问题,对既有隧道进行爆破震动速度监测以及数据分析。分别使用传统萨道夫斯基线性回归方法以及BP神经网络来分析预测爆破震动的强度,其中在利用神经网络预测时,将隧道开挖不同区段围岩条件作为一影响参量进行分析,最后建立了爆破震速预测模型,为爆破施工单段最大装药量提供依据,并将上述流程利用GIS技术集成,为爆破施工参数选取提供及时可靠依据。

Considering that the blasting excavation of a new tunnel may affect the service pertormance of the old tunnel in a tunnel expansion project,the blasting vibration monitoring and corresponding analysis of the existing tunnel are carried out. Using the traditional Sa Rodolfo J Ki method of linear regression and BP neural network,and while using neural network to predict the blasting vibration intensity,the excavation of tunnel surrounding rock condition in different sections as a parametric analysis. Finally,established a speed prediction model of blasting earthquake,providing the basis for the single maximum charge for blasting construction,and the process integrated with GIS technology, providing a reliable basis for the selection of blasting parameters.