Fundamental Theroy and Experimental Research

Rock mass quality classification based on PCA and Fisher discrimination analysis

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  • 1. School of Resources and Environment Engineering, Wuhan University of Technology, Wuhan, Hubei 430070, China; 2. School of Resources and Safety Engineering, Central South University, Changsha, Hunan 410083, China; 3. Tongshankou Copper Mine, Daye Nonferrous Metals Co., Ltd. Huangshi, Hubei 435112, China; 4. Sinosteel Corporation Wuhan Safety and Environmental Protection Research Institute, Wuhan, Hubei 430081, China

Received date: 2016-07-01

  Online published: 2018-06-09

Supported by

This work was supported by the Nature Science Foundation of Hubei Province(2015CFA136), Fundamental Research Funds for the Central Universities (2015-Ⅲ-011), and National Natural Science Foundation of China(5114112).

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.

Cite this article

QIAN Zhao-ming, REN Gao-feng, CHU Fu-jiao, QIN Shao-bing, . Rock mass quality classification based on PCA and Fisher discrimination analysis[J]. Rock and Soil Mechanics, 2016 , 37(S2) : 427 -432 . DOI: 10.16285/j.rsm.2016.S2.056

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