基于最小一乘法的露天矿爆破振动预测

Blast Induced Vibration Prediction in Open-Pit Mines Based on Least Absolute Deviation

为了提高爆破质点振动速度和主振频率经验公式的预测精度,以某露天矿山爆破振动20组监测数据为例,提出了采用灰色综合关联度分析影响质点振动速度和主振频率的关键因素,并利用最小一乘法求解不同经验公式一元线性回归方程参数的方法。研究结果表明:最大段药量、爆心距、高程、孔数以及总药量是影响质点振动速度和主振频率的重要因素,与最小二乘法相比,最小一乘法拟合的经验公式一元线性回归方程预测精度较好,不仅为露天矿爆破振动预测研究提供了理论支持,也为最小一乘法理论的发展提供了实际工程应用。

In order to improve the prediction accuracy of empirical formulas for blast induced particle velocity and dominant frequency,this study takes 20 sets of monitoring data from blasting vibrations in a certain opetrpit mine as an example.The Grey Correlation Analysis method was proposed to analyze the key factors affecting the particle velocity and dominant frequency.Additionally.the method of the Least Absolute Deviation(LAD)was employed to solve the parameters of one variable linear regression equations for different empirical formulas.The research results indicate that the maximum explosive charge per delay,blasthole burden.bench elevation,number of blastholes.and total explosive quantity are crucial factors influencing particle velocity and dominant frequency.In comparison to the Least Squares Method,the LAD-fitted empirical formulas exhibit better prediction accuracy in one variable linear regression equations.This not only provides theoretical support for blast induced vibration prediction in open-pit mines but also contributes to the practical engineering application of the Least Absolute Deviation theory.