基于BP神经网络法某公路隧道围岩稳定性研究

Tunnel Surrounding Rock Classification Model Based on BP Neural Network Method

如何简单、高效、准确地对工程岩体进行分类是一个具有挑战性的研究课题,也是现场施工的迫切需求,特别是某些特定的地下工程。以江西某公路隧道为研究对象,结合该地区实际所处的地质环境,选取不连续结构面状态及充填情况、岩石单轴抗压强度Rc、岩石质量指标RQD、地下水渗水量W和洞轴线与层状岩石的夹角θ这五个指标作为评价因子,建立了基于BP神经网络的公路隧洞围岩分类模型,成功地对公路隧道围岩等级进行了评级,取得了良好的评价效果,为公路隧道围岩的快速分类提供了依据。

How to classify engineering rock mass simply,efficiently and accurately is a challenging research topic and an urgent need for on-site construction,especially for certain underground projects.This paper takes a highway tunnel in Jiangxi as the research object,and combines the actual geological environment of the region,selects the discontinuous structural surface state and filling condition,rock uniaxial compressive strength Rc,rock quality index RQD,groundwater seepage volume W of hole axisthe angle with the layered rock the five indicators of are used as the evaluation factors.The classification model of the surrounding rock of the highway tunnel based on BP neural network is established.The grade of the surrounding rock of the highway tunnel is successfully graded and a good evaluation result is obtained.The rapid classification of surrounding rock of highway tunnels provides the basis.