岩溶区公路隧道围岩分级专家系统研发与应用
发布时间：2019-02-12 20:10
【摘要】：围岩分级是公路隧道建设的基础,它的准确划分对隧道结构的优化设计和施工的安全保障具有重要意义。但在岩溶区公路隧道建设中,由于工程地质条件的复杂性和岩溶发育的影响,对围岩级别进行准确判定是比较困难的,当前也缺少针对这一特殊围岩的分级方法,这严重阻碍了岩溶公路隧道建设的发展。 本文在国内外常用围岩分级指标体系的基础上,结合岩溶围岩的特殊性,提出了适用于岩溶区公路隧道建设的围岩分级指标体系,该指标体系包含岩石坚硬强度、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,并提出了各指标的获取方法。然后,利用建立的指标体系,以瑶寨隧道、天生桥隧道、关上二号隧道为依托工程,构建了神经网络专家知识库,并通过遗传神经网络数学理论,采用数值计算软件MATLAB构造了岩溶围岩分级专家系统模型。随后,利用MATLAB与C++混合编程技术,以遗传围岩分级模型为核心,基于Visual C++6.0开发平台,完成了岩溶区公路隧道围岩分级专家系统的研制。 为验证该专家系统的可靠性,将其应用于靖那高速公路,并与实际结果进行对比。实践表明,本专家系统围岩分级准确率达到了80.89%,基本可以满足隧道工程建设的需要。
[Abstract]:The classification of surrounding rock is the foundation of highway tunnel construction, and its accurate division is of great significance to the optimal design of tunnel structure and the safety guarantee of construction. However, in the construction of highway tunnel in karst area, due to the complexity of engineering geological conditions and the influence of karst development, it is difficult to determine the grade of surrounding rock accurately. At present, there is a lack of classification method for this special surrounding rock. This seriously hinders the development of karst highway tunnel construction. Based on the commonly used classification index system of surrounding rock at home and abroad and the particularity of karst surrounding rock, this paper puts forward a classification index system of surrounding rock for highway tunnel construction in karst area, which includes the hard strength of rock. The degree of integrity of rock mass, the state of groundwater, the occurrence of structural plane and the karst state are five indexes, and the methods of obtaining each index are put forward. Then, the expert knowledge base of neural network is constructed based on the project of Yao Zhai tunnel, Tianshengqiao tunnel and Guansheng2 tunnel, and the mathematical theory of genetic neural network is adopted. An expert system model for classification of karst surrounding rock is constructed by numerical calculation software MATLAB. Then, using the mixed programming technology of MATLAB and C, taking the genetic surrounding rock classification model as the core, and based on the development platform of Visual C 6.0, the expert system of surrounding rock classification of highway tunnel in karst area is developed. In order to verify the reliability of the expert system, it is applied to Jingna Expressway and compared with the actual results. The practice shows that the classification accuracy of the expert system reaches 80.89, which can basically meet the needs of tunnel construction.
【学位授予单位】：广西大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP182;U452.12
本文编号：2420748
[Abstract]:The classification of surrounding rock is the foundation of highway tunnel construction, and its accurate division is of great significance to the optimal design of tunnel structure and the safety guarantee of construction. However, in the construction of highway tunnel in karst area, due to the complexity of engineering geological conditions and the influence of karst development, it is difficult to determine the grade of surrounding rock accurately. At present, there is a lack of classification method for this special surrounding rock. This seriously hinders the development of karst highway tunnel construction. Based on the commonly used classification index system of surrounding rock at home and abroad and the particularity of karst surrounding rock, this paper puts forward a classification index system of surrounding rock for highway tunnel construction in karst area, which includes the hard strength of rock. The degree of integrity of rock mass, the state of groundwater, the occurrence of structural plane and the karst state are five indexes, and the methods of obtaining each index are put forward. Then, the expert knowledge base of neural network is constructed based on the project of Yao Zhai tunnel, Tianshengqiao tunnel and Guansheng2 tunnel, and the mathematical theory of genetic neural network is adopted. An expert system model for classification of karst surrounding rock is constructed by numerical calculation software MATLAB. Then, using the mixed programming technology of MATLAB and C, taking the genetic surrounding rock classification model as the core, and based on the development platform of Visual C 6.0, the expert system of surrounding rock classification of highway tunnel in karst area is developed. In order to verify the reliability of the expert system, it is applied to Jingna Expressway and compared with the actual results. The practice shows that the classification accuracy of the expert system reaches 80.89, which can basically meet the needs of tunnel construction.
【学位授予单位】：广西大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP182;U452.12
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