摘要
围岩质量是影响隧道安全的重要因素。以新疆东天山隧道工程为研究对象,采用隧道地震波法、TSP物探指标敏感性分析法和BP神经网络关联分析理论,对影响隧道围岩质量的因素进行分析,并对围岩质量进行预测。结果表明,在TSP物探众多指标中,波速V、纵横波速比V/V、泊松比μ和密度ρ是围岩质量的主控因素;BP神经网络预测围岩质量方法是可靠准确的,且预测结果可根据技术和数据的完善进一步改善;提高纵波速V、横波速V和泊松比μ的预测精度,可有效控制TSP物探指标整体预测结果。
The quality of surrounding rock is an important factor affecting the safety of tunnel.Taking Xinjiang East Tianshan Tunnel project as the research object,the factors affecting the quality of tunnel surrounding rock are analyzed and the quality of surrounding rock is predicted by using the tunnel seismic wave method,TSP geophysical index sensitivity analysis method and BP neural network correlation analysis theory.The results show that,(a)among the TSP geophysical index,the wave velocity V,P/S wave velocity ratio V/V,Poisson’s ratioμand densityρare the main controlling factor of surrounding rock quality;(b)the method of BP neural network to predict the quality of surrounding rock is reliable and accurate,and the prediction results can be further improved according to the improvement of technology and data;and(c)the increase of prediction accuracy of P-wave velocity V,S-wave velocity Vand Poisson’s ratioμcan effectively control the overall prediction results of TSP geophysical index.
作者
刘学军
高玉峰
贺一凡
姜兆东
LIU Xuejun;GAO Yufeng;HE Yifan;JIANG Zhaodong(Xinjiang Institute of Architectural Sciences(Co.,Ltd.),Urumqi 830002,Xinjiang,China;School of Civil Engineering and Architecture,Xinjiang University,Urumqi 830046,Xinjiang,China)
出处
《水力发电》
CAS
2022年第9期51-55,共5页
Water Power
基金
国家级大学生创新训练计划项目(202010755097)
新疆维吾尔自治区重大科技专项课题(2018A03003-1)。
关键词
隧道工程
围岩质量预测
地震波法
TSP物探指标
BP神经网络
力学参数
tunnel engineering
surrounding rock quality prediction
seismic wave method
TSP geophysical index
BP neural network
mechanical parameter
