摘要
为研究隧道超前地质预报中溶洞的探地雷达的数据特征,可从时间剖面、三瞬属性(瞬时振幅、瞬时相位、瞬时频率)以及时频联合分布等方面进行特征分析。利用电磁波时域有限差分法进行数值模拟,得出溶洞在探地雷达时间剖面中呈现出双曲线特征,溶洞的填充情况不同,反射波振幅的幅值和方向不同。探地雷达数据的瞬时属性中,瞬时振幅可凸显出溶洞的反射,瞬时相位可作为溶洞填充情况的判断依据,瞬时频率可作为溶洞的辅助判别标志。时频联合分布中,电磁波能量集中于溶洞顶的反射波位置,无填充溶洞的电磁波能量呈现出多个块状的分布区域,并出现拖尾现象,充水溶洞的电磁波能量集中分布在一个区域。通过对溶洞的实测数据进行分析,进一步验证了溶洞探地雷达数据时频域特征的有效性。
In order to investigate the characteristics of the ground penetrating radar(GPR)data for tunnel geological forecast of karst caves,the time profile,instantaneous attributes(instantaneous amplitude,phase,and frequency)and time-frequency spectrum are proposed to inspect CPR data.From numerical simulations performed by the finite-difference time-domain(FDTD)method,a hyperbola can well mark a karst cave in the time profile.The amplitude and direction of reflected waves are different with different fillings.Among the instantaneous properties,the instantaneous amplitude can highlight the reflections from karst caves,the instantaneous phase can indicate the filling material,and the instantaneous frequency can be used as a secondary indicator.In the time-frequency spectrum,the energy is concentrated to the karst cave area.Multiple energy areas can be observed for air-flled karst caves,and a single energy area can be observed for water-filled karst caves.By the analysis of real data gathered from geological conditions of karst caves,the proposed time and frequency characteristics are further validated.
作者
余世为
牛刚
覃晖
张东昊
王峥峥
Yu Shiwei;Niu Gang;Qin Hui;Zhang Donghao;Wang Zhengzheng(Shenzhen Municipal Design&Research Institute Co.,Ltd.,Shenzhen 518000,China;CCCC Channel Construction Investment Development Co.,Ltd.,Fuzhou 350000,China;School of Civil Engineering,Dalian University of Technology,Dalian 116024,China;Research Institute of Dalian University of Technology in Shenzhen,Shenzhen 518057,China)
出处
《工程勘察》
2023年第10期67-72,共6页
Geotechnical Investigation & Surveying
基金
国家自然科学基金项目(41904095)
深圳市中央引导地方科技发展专项资金资助项目(2021Szvup020)。
关键词
隧道
超前地质预报
溶洞
探地雷达
时频分析
数值模拟
tunnel
geological forecast
karst
ground penetrating radar(GPR)
time-frequency analysis
numerical simulation