【摘要】 以某工程不同爆点不同监测点的爆破振动监测数据为背景 ,在分析爆破振动主要影响因素的基础上 ,建立了能同时对爆破振动速度峰值、振动主频率和振动的持续时间进行预报的BP神经网络模型。该模型的预报结果 (爆破振动的幅值、振动主频率和振动持续时间 )与实际监测结果基本吻合 ,从而得到了该场地不同地质、地形情况下爆破振动预报的BP神经网络模型。更多还原

【Abstract】 On the basis of main factors analysis that affect blasting vibration in an engineering project, a BP neural network model was established to predict the peak value, main frequency and duration time of blasting vibration in several different sites. Vibration monitor records at the work sites were used as training set. The trained neural network can predict blast vibration parameters in accordance with monitor data.更多还原