| 岩溶区公路隧道围岩分级专家系统设计与应用 |
| |
| 引用本文： | 江杰,蒲鸥,欧孝夺,赵建刚,谢规球.岩溶区公路隧道围岩分级专家系统设计与应用[J].长江科学院院报,2018,35(7):94-99. |
| |
| 作者姓名： | 江杰 蒲鸥 欧孝夺 赵建刚 谢规球 |
| |
| 作者单位： | 1.广西大学 a.土木建筑工程学院; b.工程防灾与结构安全重点实验室,南宁 530004;2.桂林理工大学广西岩土力学与工程重点实验室,广西 桂林 541004;3.中交第四公路工程局有限公司,北京 100022 |
| |
| 基金项目： | 国家自然科学基金项目(51568006;51768006)，中国博士后科学基金项目(2017M612865)，广西岩土力学与工程重点实验室资助课题(14-KF-03) |
| |
| 摘 要： | 岩溶地质条件对公路隧道建设影响较大。隧道在建设过程中围岩分级除考虑常用指标外,还须考虑岩溶影响因素指标。以广西岩溶区实际工程为背景,提出了考虑多因素的岩溶状态指标分析方法,建立以岩石坚硬程度、岩体完整程度、地下水状态、结构面产状和岩溶状态5个指标的围岩分级模型。根据MatLab和C++的软件平台设计,植入分级指标参数归一化算法,结合广西瑶寨等3个隧道工程,建立了神经网络专家知识库。最后对专家系统软件进行工程应用,软件判别与实际勘察判别一致性达到80.89%,工程应用效果良好。
|
| 关 键 词： | 岩溶 公路隧道 围岩分级 专家系统 神经网络 |
| 收稿时间： | 2016-11-23 |
Expert System of Surrounding Rock Classification for Highway Tunnel in Karst Region: Design and Application |
| |
| JIANG Jie,PU Ou,OU Xiao-duo,ZHAO Jian-gang,XIE Gui-qiu.Expert System of Surrounding Rock Classification for Highway Tunnel in Karst Region: Design and Application[J].Journal of Yangtze River Scientific Research Institute,2018,35(7):94-99. |
| |
| Authors: | JIANG Jie PU Ou OU Xiao-duo ZHAO Jian-gang XIE Gui-qiu |
| |
| Affiliation: | 1.College of Civil Engineering and Architecture, Guangxi University,Nanning 530004, China;2.Key Laboratory of Disaster Prevention and Structural Safety, Guangxi University,Nanning 530004, China;3.Guangxi Provincial Key Laboratory of Geomechanics and Geotechnical Engineering, Guilin University ofTechnology, Guilin 541004, China; 4.CCCC Fourth Highway Engineering Co.,Ltd.,Beijing 100022, China |
| |
| Abstract: | As highway tunnel construction is greatly affected by karst geological condition, karst indexes should be considered in addition to conventional indicators in surrounding rock classification. In this research, a model of surrounding rock classification was set up, in which rock hardness, rock mass integrity, groundwater status, structural plane occurrence and karst status are included. The expert system based on three tunnel projects in Guangxi Province for surrounding rock classification was designed by embedding normalization algorithm for the indexes using MatLab and C++. The expert system software was applied to engineering and the consistence between software results and actual survey reached 80.89%. |
| |
| Keywords: | karst highway tunnel classification of surrounding rock expert system neural network |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
| 点击此处可从《长江科学院院报》浏览原始摘要信息 |
|
点击此处可从《长江科学院院报》下载全文 |
|
