基于模糊神经网络的水工隧洞病害诊断研究  

Defects Diagnosis of Hydraulic Engineering Tunnel Based on Fuzzy Neural Network

作　　者：王桂平[1] 朱苦竹[2] 

机构地区：[1]同济大学地下建筑与工程系,上海20092 [2]桂林工学院土木系,广西桂林541004

出　　处：《地下空间与工程学报》2009年第1期201-206,共6页Chinese Journal of Underground Space and Engineering

基　　金：教育部新世纪优秀人才支持计划资助(NCET-05-0386)

摘　　要：引入基于模糊神经网络的综合评判方法,参照铁路、公路隧道的研究成果,构建了水工隧洞病害综合诊断指标体系,划分了水工隧洞安全等级,给出了诊断指标的判定标准,采用改进的层次分析法分析了诊断指标的权重,建立了水工隧洞病害诊断的模糊评价模型,并应用于工程实际,取得了比较符合实际的结论,证实了该方法在工程应用中的可用性。By research of railway and highway tunnels, this thesis introduced composite evaluation method for defect diagnosis based on fuzzy neural network, an integrative index system of defects diagnosis in hydraulic tunnel is established, the safety grade of hydraulic tunnel is divided, the diagnosis index＇s judgment standard is provided, the weight of diagnosis index is analyzed by adopting improved analytic hierarchy process, the fuzzy evaluation model of defects diagnosis is established, and this method was applied to one project. The results indicated that the conclusion conformed to the engineering practice, and verified the method＇s suitability.

关 键 词：水工隧洞 病害诊断 模糊 神经网络 安全分级 

分 类 号：U45[建筑科学—桥梁与隧道工程]