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The geological strength index(GSI) system,widely used for the design and practice of mining process,is a unique rock mass classification system related to the rock mass strength and deformation parameters based on the generalized Hoek-Brown and Mohr-Coulomb failure criteria.The GSI can be estimated using standard chart and field observations of rock mass blockiness and discontinuity surface conditions.The GSI value gives a numerical representation of the overall geotechnical quality of the rock mass.In this study,we propose a method to determine the GSI quantitatively using photographic images of in situ jointed rock mass with image processing technology,fractal theory and artificial neural network(ANN).We employ the GSI system to characterize the jointed rock mass around the working in a coal mine.The relative error between the proposed value and the given value in the GSI chart is less than 3.6%.
The geological strength index (GSI) system, widely used for the design and practice of mining process, is a unique rock mass classification system related to the rock mass strength and deformation parameters based on the generalized Hoek-Brown and Mohr-Coulomb failure criteria. The GSI can be estimated using standard chart and field observations of rock mass blockiness and discontinuity surface conditions. GSI value gives a numerical representation of the overall geotechnical quality of the rock mass. In this study, we propose a method to determine the GSI quantitatively using photographic images of in situ jointed rock mass with image processing technology, fractal theory and artificial neural network (ANN) .We employ the GSI system to characterize the jointed rock mass around the working in a coal mine. the relative error between the proposed value and the given value in the GSI chart is less than 3.6%.