摘要
当前高速公路路基爆破的智慧化水平较低,导致路基深孔爆破时爆破振速难以实现精准预测,爆破施工优化效果较差。依托济青中线潍青段路基深孔爆破工程,引入无人机航测技术,建立路基爆破的三维模型,提出基于无人机摄影量测和三维模型重建技术的爆心距计算方法,实现了路基深孔爆破的爆心距精准计算;通过爆破振动监测获取振速数据,基于药量、振速、爆心距等参数建立深孔路基爆破的振速预测方法,有效提高爆破振速预测公式的拟合度和精准度,为路基爆破智慧化设计优化、施工决策及现场安全管理提供科学依据。
At present,the intelligent level of highway subgrade blasting is low,which makes it difficult to accurately predict the blasting vibration velocity during deep hole blasting of subgrade,and the optimization effect of blasting construction is poor.Based on the deep hole blasting project of Weiqing section of Jiqing Middle Line,the un⁃manned air vehicle(UAV)aerial survey technology is introduced to establish the three-dimensional model of sub⁃grade blasting.The calculation method of blasting center distance based on UAV photogrammetry and three-dimen⁃sional model reconstruction technology is proposed,and the accurate calculation of blasting center distance of deep hole blasting of subgrade is realized.The vibration velocity data are obtained through blasting vibration monitoring,and the vibration velocity prediction method of deep hole subgrade blasting is established based on the parameters such as charge,vibration velocity and blasting center distance,which effectively improved the fitting degree and ac⁃curacy of the prediction formula of blasting vibration velocity,providing a scientific basis for the intelligent design optimization,construction decision-making,and on-site safety management of subgrade blasting.
作者
刘慧宁
孙术源
胡婧煜
朱玉震
管晓明
LIU Huining;SUN Shuyuan;HU Jingyu;ZHU Yuzhen;GUAN Xiaoming(Shandong HI-speed Engineering Construction Group Co.,Ltd.,Jinan 250014,China;Yantai Qixia Highway Construction and Maintenance Center Yantai 265399,China;School of Engineering,University of Birmingham,Birmingham,B152TT,United Kingdom;Qingdao University of Technology,School of Civil Engineering,Shandong Qingdao 266520,China)
出处
《低温建筑技术》
2024年第1期64-68,共5页
Low Temperature Architecture Technology
关键词
路基爆破
无人机摄影量测
爆心距
振速预测
subgrade blasting
UAV photogrammetry
explosive center distance
vibration velocity prediction