BP神经网络在隧道监控量测数据处理中的应用  

Application of BP Neural Network on Monitoring Data Processing of Tunnel

作　　者：谢仁红[1] 邹朋高 文辉辉[1] 

机构地区：[1]中交四航工程研究院有限公司中交交通基础工程环保与安全重点实验室,广东广州510230 [2]中交四航局第三工程有限公司,广东湛江524005

出　　处：《水力发电》2013年第9期20-22,48,共4页Water Power

摘　　要：为保证某高速公路隧道开挖过程中的施工安全,在优化围岩变形监测方案与预警方法的基础上,采用BP神经网络对典型监测断面位移量测数据进行了回归分析。结果表明,BP神经网络模型预测值能较好地拟合拱顶沉降和周边收敛位移实测值,可以作为围岩稳定性判定和确定二次衬砌施工时间的依据,具有重要的经济性和实用性。To ensure the construction safety of tunnel in an expressway, the monitoring programs and early warning methods for surrounding rock deformation are optimized, and the BP neural network is introduced for regression analysis of measured deformation data of typical monitoring sections. The resuhs show that the regression values match well with actual roof settlement and peripheral convergence deformation measuring values. The regression values can be as the basis of evaluating surrounding rock stability and determining secondary lining time, which is economic and practical.

关 键 词：BP神经网络 围岩变形 安全监测 回归分析 

分 类 号：TU457[建筑科学—岩土工程]