谷歌浏览器插件
订阅小程序
在清言上使用

Quantitative granitic weathering assessment for rock mass classification optimization of tunnel face using image analysis technique

Intan Norsheira Yusoff, Mohd Ashraf Mohamad Ismail, Hayato Tobe, Kensuke Date, Yasuhiro Yokota

Ain Shams Engineering Journal/Ain Shams Engineering Journal(2023)

引用 5|浏览5
暂无评分
摘要
Weathering degree is one of the key criteria used to determine tunnel support with the main difficulty is in assessing the weathering grade of the tunnel face. This study applied CIEL*a*b colour space and image analysis to a rock mass tunnel face. The authors used the Japanese Highway (JH) Rock Mass Classification System to classify the rock mass tunnel face. JudGeo converted the RGB photographs to L*a*b values. This study compared the quantitative evaluation system's performance to manual tunnel face mapping by geologists using six JH Rock Mass Classification samples (Class B, CI, CII, DI, DII, and E). The analysis sho-wed good correlations between four (B; CI; CII; DI) of six rock mass classes. The tunnel face mapping showed two rock mass classes above grade (DII and E). This technique can effectively identify the degree of weathering grades of the tunnel face, especially for fresh to moderately weathered tunnel faces.(c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams University
更多
查看译文
关键词
Decision support systems,Rock mass classification,Image analysis,Tunneling,Weathering
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要