Fuzzy Clustering Analysis and Application of the Degree of Difficulty of Coal Seam Water Injection

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Abstract:

The degree of difficulty of coal seam water infusion is the important basis of pouring water into coal beds, by fully analyzing influence factors of the degree of difficulty of pouring water into coal beds, the main influence factors of pouring water into coal beds was determined and the fuzzy clustering analysis model was build which base on the depth of burying of the coal seam, crack growth degree, porosity, moist edge, water saturation value-added and consistent coefficient. By comparing evaluation result of this model with Fisher evaluation result, the model result is accuracy and reliability. According to this model to predict South decurrent 18th layer 7th face Coal Seam of Shuangyashan Mining Group Dongrong No.2 Coal Mine,the predicted results are consistent with the actual situation and offering theoretical guidance to the choice of injection water parameters .

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Periodical:

Advanced Materials Research (Volumes 962-965)

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939-945

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June 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Zhang Yongji and Li Zhande, Qin Weihan. Coal seam water injection technology [M]. Beijing: Publishing House of the coal industry, 2001: 149-157.

Google Scholar

[2] Zhao Zheng . New development of comprehensive dust control techniques for fully mechanized coal mining face [J]. Coal engineer, 1992, 3: 46-50.

Google Scholar

[3] Zhang Yansong. Research on coal seam water infusion technology of fully mechanized caving mining face [J]. Coal science and technology, 2001, 1: 31-35.

Google Scholar

[4] Jin Longzhe, Li Jinping, Sun Yufu. Mine dust prevention and control theory [M]. Beijing: Science Press, 2010: 177-222.

Google Scholar

[5] Wang Weihu. Application status and prospect of dust prevention technique using coal seam water injection [J]. Coal science and technology, 2011, 1: 57-60.

Google Scholar

[6] Qin Shuyu and Qin Wei , Zhao Jingfu. BP neural network evaluation method of coal seam water injection difficulty [J]. Chinese Journal of geological hazard and control, 2006, 17 (3): 87-90.

Google Scholar

[7] Yuan Zhigang, Wang Hongtu and Hu Guozhong. Fisher discriminant analysis model of coal seam water infusion difficulty and its application [J]. Journal of coal, 2011, 36 (4): 638-642.

Google Scholar

[8] Guo Sizong, Chen Gang. Soft Computing method in information science [M]. Northeastern University Press, 2001, 287-292.

Google Scholar