Cheng Zhai
School of Safety Engineering, China University of Mining and Technology, 221116, Xuzhou, China
Xu Yu
School of Safety Engineering, China University of Mining and Technology, 221116, Xuzhou, China
Bai-Quan Lin
School of Safety Engineering, China University of Mining and Technology, 221116, Xuzhou, China
Wei Yang
School of Safety Engineering, China University of Mining and Technology, 221116, Xuzhou, China
ABSTRACT
Coal and gas outburst is one of the main disasters in coal mine, the outburst forecasting is the main part of prevention work which affects the prevention measures establishment and production plan directly. However, only several factors such as ground stress, gas pressure or coal structure is taken into account, the forecasting results can not be very accurate. Its urgent to get more kinds of parameters into consideration and enhance the outburst forecasting accuracy. Risk forecasting in working face is the first step of mine wit outburst andan accurate determination of the sensitive index of coal and gas outburst is very important. Aiming at the problems of low accuracy of risk forecasting and lack of proper method to determine the critical value of the outburst sensitive index, the Statistical Process Control (SPC) method was proposed, the selecting method of SPC control chart was discussed andthe drawing process of SPC control chart and the determination of critical value of the outburst sensitive index were analysed. At the same time, the three-rate method was used to analyse the field data of the outburst index and the accuracy of calculation results was proved. The results showed that the affected extent of coal is different in underground working face with the change of drilling depth, the critical value should be changed and it should be not uniformly determined as a fixed value simply. The outburst risk would lead to a dynamic change along with changes of space and time. The SPC is a dynamic forecasting method which may determine the sensitive index of outburst forecasting accurately and reduce the accident rate of the coal and gas outburst.
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How to cite this article
Cheng Zhai, Xu Yu, Bai-Quan Lin and Wei Yang, 2013. Method for Prediction of Coal and Gas Outburst Based on Data Mining Technology. Journal of Applied Sciences, 13: 3995-4000.
DOI: 10.3923/jas.2013.3995.4000
URL: https://scialert.net/abstract/?doi=jas.2013.3995.4000
DOI: 10.3923/jas.2013.3995.4000
URL: https://scialert.net/abstract/?doi=jas.2013.3995.4000