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高程影响下爆破振动速度衰减模型优选研究 被引量:4

Preferred Model for Blast Vibration Velocity Attenuation under the Influence of Elevation
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摘要 准确预测爆破振动速度是控制爆破危害的重要内容。为了优选高程影响的质点峰值振速预测模型,基于量纲分析理论,综合考虑了测点与爆源之间的位置信息,重构了峰值振速预测公式。以鞍千矿业露天台阶爆破作业为背景,进行爆破振动监测试验,通过线性与非线性回归拟合法分析不同峰值振速预测模型的适用性。结果表明,考虑高程影响的预测经验公式预测精度均大于萨道夫斯基公式;结合测点与爆区之间的直线距离、水平距离和高程差的预测经验公式的预测精度高于其他预测经验公式;推导的预测模型可以较为准确地预测峰值振速,预测精度为91.60%;非线性回归得出考虑高程影响的预测模型可以更好地表征爆破振动在边坡岩体中的传播规律;优选了适用性较好的峰值振速预测模型,预测精度为91.87%。 Accurate prediction of blast vibration velocity is an important component of blast hazard control.In order to optimize the elevation-influenced mass peak vibration velocity prediction model,the peak vibration velocity prediction equation is reconstructed based on the gauge analysis theory,taking into account the location information between the measurement point and the explosion source.Blasting vibration monitoring test in the context of the open-pit bench blasting at Anqian Mine.The applicability of different peak vibration prediction models is legally analyzed by linear and nonlinear regression.The results show that the prediction accuracy of the empirical formulas for prediction considering the effect of elevation are all greater than that of the Sadovsky formula.Empirical formula for prediction which combines the straight-line distance,horizontal distance and elevation difference between the measuring point and the burst area is more accurate than other empirical formulas.The derived prediction model can predict the peak vibration speed more accurately,with a prediction accuracy of 91.60%.Non-linear regression to derive a prediction model that takes into account the effect of elevation can better characterize the propagation pattern of blast vibration in slope rock masses.The peak vibration speed prediction model with better applicability was preferred,and the prediction accuracy is 91.87%.
作者 包松 郭连军 莫宏毅 任碧琦 徐振洋 BAO Song;GUO Lianjun;MO Hongyi;REN Biqi;XU Zhenyang(School of Mining Engineering,University of Science and Technology Liaoning,Anshan 114051,China;Engineering Research Center of Green Mining of Metal Mineral Resources,Liaoning Province,Anshan 114051,China;School of Architecture and Civil Engineering,Shenyang University of Technology,Shenyang 110870,China)
出处 《有色金属工程》 CAS 北大核心 2022年第9期115-121,共7页 Nonferrous Metals Engineering
基金 辽宁省教育厅重点项目(LJKZ0282)。
关键词 爆破振动 峰值振速 高程影响 预测模型 线性与非线性回归 blast vibration peak vibration velocity elevation impact predictive model linear and non-linear regression
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