Quantitative granitic weathering assessment for rock mass classification optimization of tunnel face using image analysis technique
Ain Shams Engineering Journal/Ain Shams Engineering Journal(2023)
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
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关键词
Decision support systems,Rock mass classification,Image analysis,Tunneling,Weathering
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