关键词: 岩体质量分级, 主成分分析（PCA）, Fisher判别分析

Abstract: Rock mass quality classification plays a very important role in the practical engineering. Based on the combination of principal component analysis(PCA) and Fisher discrimination analysis method, a rock mass quality grade discriminant model is established. Uniaxial compressive strength, rock volumetric joint count, sonic compressional wave velocity, the jointed surface weathering coefficient of variation, the jointed surface roughness coefficient and permeability coefficient are selected as the discrimination factor of the rock mass quality classification. 20 training samples were selected from engineering rock characteristics data in the area of open pit of Yongping Copper Mine and 10 test samples is used to test the model and application. Moreover, comparing with the traditional RMR law and Fisher discriminant analysis, the corresponding correctness rates are 87%, 70%, 77%. The results show that: the combination of principal component analysis and Fisher discrimination analysis method is more accurate than the traditional one.

Key words: rock mass quality classification, principal component analysis(PCA), Fisher discrimination analysis