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| ESTABLISHING PREDICTIVE MODEL FOR ROCK UNIAXIAL COMPRESSIVE STRENGTH OF NO.11–2 COAL SEAM ROOF IN HUAINAN MINING AREA |
| YANG Ke1，2，3，YUAN Liang1，3，QI Lianguang1，2，LIAO Binchen3 |
| (1. Anhui Key Laboratory of Integrated Coal Exploitation and Gas Extraction，Anhui University of Science and Technology，Huainan，Anhui 232001，China；2. Key Laboratory for Coal Mine Safety and Efficient Exploitation Jointly Built by Anhui Province and Ministry of Education，Anhui University of Science and Technology，Huainan，Anhui 232001，China；3. Huainan Mining Industry(Group) Co.，Ltd.，Huainan，Anhui 232001，China) |
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Abstract In order to investigate the relationship between uniaxial compressive strength(UCS) and elastic modulus of mudstone and sandstone in coal bearing strata，the uniaxial compressive tests of rock in No.11–2 coal seam roof of Gubei coal mine in Huainan mining area are conducted；and then 120 groups test data are obtained. Regarding the UCS as the dependent variable and the elastic modulus as the independent variable，six regression equations are proposed through the professional mathematical statistics software SPSS19.0，which are linear function，logarithmic function，quadratic function，cubic function，exponential function and power function respectively. The best nonlinear regression predictive model of the uniaxial compressive strength，namely quadratic regression equation，is established based on statistical analyses，which are regression equation significant test，regression coefficients significant test，goodness-of-fit test for regression equation，D-W inspection，linear regression equation of inspection，normality test and randomness test. Finally，the nonlinear regression predictive model is used to forecast the rock UCS in the No.11–2 coal seam roof of Zhangji and Pan?er coal mines in Huainan mining area. Comparative results show that the predicted values and the tested values are in good agreement and the model could be used to predict rock mechanical parameters in similar coal bearing strata.
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Received: 03 June 2013
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2013, Vol. 32 
