摘要
为揭示岩爆与声发射现象之间的关系,以莱州花岗岩为例采用应变岩爆物理模拟试验系统进行了室内岩爆试验。对实时采集的声发射信号首先进行预处理,然后进行大数据可视化分析。结果表明:试验过程中声发射信号的主频主要分布在中低频、中频、中高频这3个频带;声发射信号的振幅和能量试验初期和中期变化较小,后期变化大且呈现先增大后减小的变化规律。研究成果可用于隧道岩爆预测。
In order to reveal the relationship between rockburst and acoustic emission,taking Laizhou granite as an example,the laboratory rockburst test was carried out by using the strain rockburst physical simulation test system.The acoustic emission signals collected in real-time were preprocessed first,and then the big data visual analysis was carried out.The results show that the main frequency of the acoustic emission signal during the experiment is mainly distributed in the three frequency bands of medium-low frequency,medium frequency and medium-high frequency.The amplitude and energy of acoustic emission signal change slightly in the early and middle stage of the test,and change greatly in the later stage,and show the change law of first increasing and then decreasing.The research results can be used for tunnel rockburst prediction.
作者
张昱
李继涛
苏仡琳
高凯龙
刘开峰
ZHANG Yu;LI Jitao;SU Yilin;GAO Kailong;LIU Kaifeng(School of Electrical Engineering and Information Technique,Beijing University of Civil Engineering and Architecture,Beijing 100044,China;Beijing Key Laboratory of Intelligent Processing for Building Big Data,Beijing University of Civil Engineering and Architecture,Beijing 100044,China;State Key Laboratory for GeoMechanics and Deep Underground Engineering,China University of Mining and Technology(Beijing),Beijing 100083,China)
出处
《铁道建筑》
北大核心
2021年第8期84-87,共4页
Railway Engineering
基金
国家重点研发计划(2016YFC0600901)
北京中矿创新联盟能源环境科学研究院基金(00362016055)
北京建筑大学研究生创新项目(PG2021054)。
关键词
铁路隧道
岩爆预测
试验研究
莱州花岗岩
声发射
快速傅里叶变换
大数据
可视化分析
railway tunnel
rockburst prediction
experimental study
Laizhou granite
acoustic emission
fast Fourier transform
big data
visual analysis
