巖溶區(qū)公路隧道圍巖分級(jí)專家系統(tǒng)研發(fā)與應(yīng)用
[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.
【學(xué)位授予單位】:廣西大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2014
【分類號(hào)】:TP182;U452.12
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 閆天俊;吳雪婷;吳立;;地下洞室圍巖分類相關(guān)性研究與工程應(yīng)用[J];地下空間與工程學(xué)報(bào);2009年06期
2 李天斌;王睿;;ART1神經(jīng)網(wǎng)絡(luò)在隧道圍巖分類中的應(yīng)用[J];成都理工大學(xué)學(xué)報(bào)(自然科學(xué)版);2006年05期
3 宋戰(zhàn)平;黨宏斌;李寧;;既有溶洞對(duì)隧道圍巖位移特征影響的數(shù)值試驗(yàn)[J];長(zhǎng)江科學(xué)院院報(bào);2008年05期
4 趙明階,敖建華,劉緒華,王彪;隧道底部溶洞對(duì)圍巖變形特性的影響分析[J];重慶交通學(xué)院學(xué)報(bào);2003年02期
5 雷金山;蘇鋒;陽(yáng)軍生;陳福全;周燦朗;;土洞對(duì)地鐵隧道開(kāi)挖的影響性狀研究[J];鐵道科學(xué)與工程學(xué)報(bào);2008年02期
6 左昌群;陳建平;;基于可拓學(xué)理論的圍巖分級(jí)方法在變質(zhì)軟巖隧道中的應(yīng)用[J];地質(zhì)科技情報(bào);2007年03期
7 牛文林;李天斌;熊國(guó)斌;張廣洋;;基于支持向量機(jī)的圍巖定性智能分級(jí)研究[J];工程地質(zhì)學(xué)報(bào);2011年01期
8 李華;焦彥杰;;基于RMR的模糊AHP法在巖體分級(jí)中的應(yīng)用[J];工程地質(zhì)學(xué)報(bào);2011年05期
9 蔣樹(shù)屏,丁浩,涂耘;巖溶地質(zhì)特長(zhǎng)隧道的關(guān)鍵技術(shù)問(wèn)題及對(duì)策[J];公路交通技術(shù);2005年05期
10 師偉;史彥文;韓常領(lǐng);曹校勇;;RMR圍巖分級(jí)法與中國(guó)公路隧道圍巖分級(jí)方法對(duì)比[J];中外公路;2009年04期
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