A Fisher’s Criterion-Based Linear Discriminant Analysis for Predicting the Critical Values of Coal and Gas Outbursts Using the Initial Gas Flow in a Borehole

The risk of coal and gas outbursts can be predicted using a method that is linear and continuous and based on the initial gas flow in the borehole (IGFB); this method is significantly superior to the traditional point prediction method. Acquiring accurate critical values is the key to ensuring accurate predictions. Based on ideal rock cross-cut coal uncovering model, the IGFB measurement device was developed. The present study measured the data of the initial gas flow over 3 min in a 1 m long borehole with a diameter of 42 mm in the laboratory. A total of 48 sets of data were obtained. These data were fuzzy and chaotic. Fisher’s discrimination method was able to transform these spatial data, which were multidimensional due to the factors influencing the IGFB, into a one-dimensional function and determine its critical value. Then, by processing the data into a normal distribution, the critical values of the outbursts were analyzed using linear discriminant analysis with Fisher’s criterion. The weak and strong outbursts had critical values of 36.63 L and 80.85 L, respectively, and the accuracy of the back-discriminant analysis for the weak and strong outbursts was 94.74% and 92.86%, respectively. Eight outburst tests were simulated in the laboratory, the reverse verification accuracy was 100%, and the accuracy of the critical value was verified.

[1]  Peng Hon Improved analytic hierarchy process for coal and gas outburst prediction , 2015 .

[2]  Classification of Coal Seams for Coal and Gas Outburst Proneness in the Zonguldak Coal Basın, Turkey , 2014 .

[3]  Zhao Zhi-gang Study of premonitory time series prediction of coal and gas outbursts based on chaos theory , 2009 .

[4]  Li Sheng PATTERN RECOGNITION AND POSSIBILITY PREDICTION OF COAL AND GAS OUTBURST , 2005 .

[5]  Jia Yao-dong,et al.  STUDY ON ROCK MECHANICS IN DEEP MINING ENGINEERING , 2005 .

[6]  Song Weihua,et al.  Prediction of Coal and Gas Outburst Based on PCA-BP Neural Network , 2013 .

[7]  Hao Ji The applying of fuzzy network techniques in prediction of coal and gas outbursts , 1999 .

[8]  Wu Aijun Dynamic separation technology of drill cutting and gas in continuous flow method , 2012 .

[9]  Qin Yuepin Finite difference model of borehole gas emission and numerical simulation , 2014 .

[10]  Yu Qi Study of dynamic gas emission during boring process by using numerical simulation , 2001 .

[11]  Li Zhong-qun,et al.  Development of Coal and Gas Outburst Prediction System Based on BP Neural Network , 2012 .

[12]  N. Bai Theoretical Model of Gas Diffusion Through Coal Particles and Its Analytical Solution , 2001 .

[13]  Javier Toraño,et al.  Application of outburst risk indices in the underground coal mines by sublevel caving , 2012 .

[14]  Guo De-yong Prediction method of coal and gas outburst by analytic hierarchy process and fuzzy comprehensive evaluation , 2007 .

[15]  Zhou Li-hua,et al.  The Study on the Methods for Predicting Coal or Gas Outburst Based on BP Neural Network , 2005 .