Geomechanics and Engineering

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Hazard prediction of coal and gas outburst based on fisher discriminant analysis

  • Chen, Liang (School of Energy & Environment Engineering, Zhongyuan University of Technology) ;
  • Wang, Enyuan (Key Laboratory of Coal Methane and Fire Control, Ministry of Education, China University of Mining and Technology) ;
  • Feng, Junjun (Key Laboratory of Coal Methane and Fire Control, Ministry of Education, China University of Mining and Technology) ;
  • Wang, Xiaoran (Key Laboratory of Coal Methane and Fire Control, Ministry of Education, China University of Mining and Technology) ;
  • Li, Xuelong (Key Laboratory of Coal Methane and Fire Control, Ministry of Education, China University of Mining and Technology)
  • Received : 2015.11.19
  • Accepted : 2017.06.29
  • Published : 2017.11.25
⟨ Previous Next ⟩

Abstract

Coal and gas outburst is a serious dynamic disaster that occurs during coal mining and threatens the lives of coal miners. Currently, coal and gas outburst is commonly predicted using single indicator and its critical value. However, single indicator is unable to fully reflect all of the factors impacting outburst risk and has poor prediction accuracy. Therefore, a more accurate prediction method is necessary. In this work, we first analyzed on-site impacting factors and precursors of coal and gas outburst; then, we constructed a Fisher discriminant analysis (FDA) index system using the gas adsorption index of drilling cutting ${\Delta}h_2$, the drilling cutting weight S, the initial velocity of gas emission from borehole q, the thickness of soft coal h, and the maximum ratio of post-blasting gas emission peak to pre-blasting gas emission $B_{max}$; finally, we studied an FDA-based multiple indicators discriminant model of coal and gas outburst, and applied the discriminant model to predict coal and gas outburst. The results showed that the discriminant model has 100% prediction accuracy, even when some conventional indexes are lower than the warning criteria. The FDA method has a broad application prospects in coal and gas outburst prediction.

Keywords

Acknowledgement

Supported by : National Science Foundation of China

References

  1. Cao, Y., He, D. and Glick, D.C. (2001), "Coal and gas outburst in footwalls of reverse faults", J. Coal Geol., 48(1), 47-63. https://doi.org/10.1016/S0166-5162(01)00037-4
  2. Chen, H., Li, X., Liu, A. and Peng, S. (2009), "Identifying of mine water inrush sources by Fisher discriminant analysis method", J. Centr. South U., 40, 1114-1120.
  3. Chen, S., Liu, J. and Chen, L. (2014), "The coal and gas outburst prediction model research based on SVM", J. Earth Sci. Eng., 7, 616-623.
  4. Diaz Aguado, M.B. and Gonzalez Nicieza, C. (2007), "Control and prevention of gas outbursts in coal mines, Riosa-Olloniego coalfield, Spain", J. Coal Geol., 69(4), 253-266. https://doi.org/10.1016/j.coal.2006.05.004
  5. Ding, Y., Dou, L., Cai, W., Chen, J., Kong, Y., Su, Z. and Li, Z. (2016), "Signal characteristics of coal and rock dynamics with micro-seismic monitoring technique", J. Min. Sci. Technol., 26, 683-690. https://doi.org/10.1016/j.ijmst.2016.05.022
  6. Fernandez-Diaz, J.J., Gonzalez-Nicieza, C., Alvarez-Fernandez, M.I. and Lopez-Gayarre, F. (2013), "Analysis of gas-dynamic phenomenon in underground coal mines in the central basin of Asturias (Spain)", Eng. Fail. Anal., 34, 464-477. https://doi.org/10.1016/j.engfailanal.2013.07.027
  7. He, X., Nie, B., Chen, W., Wang, E., Dou, L., Wang, Y., Liu, M. and Mitrie, H. (2012), "Research progress on electromagnetic radiation in gas-containing coal and rock fracture and its applications", Safety Sci., 50(4), 728-735. https://doi.org/10.1016/j.ssci.2011.08.044
  8. Hu, Q., Peng, S., Xu, J., Zhang, L. and Liu, D. (2015), "Application of gray target models in the prediction of coal and gas outburst: the case of jinzhushan coal mine in China", J. Safety Secur. Eng., 5(2), 142-149. https://doi.org/10.2495/SAFE-V5-N2-142-149
  9. Huang, H., Li, J. and Liu, J. (2012), "Gene expression data classification based on improved semisupervised local Fisher discriminant analysis", Exp. Syst. Appl., 39(3), 2314-2320. https://doi.org/10.1016/j.eswa.2011.08.032
  10. Jiang, C., Xu, L., Li, X., Tang, J., Chen, Y., Tian, S. and Liu, H. (2015), "Identification model and indicator of outburst-prone coal seams", Rock Mech. Rock Eng., 48(1), 409-415. https://doi.org/10.1007/s00603-014-0558-0
  11. Li, C., Liu, Y. and Zhang, H. (2015), "An improved coal and gas outburst prediction algorithm based on BP neural network", J. Contr. Autom., 8(6), 169-176.
  12. Li, X. and Zhou, W. (2012), "The risk forecast of coal and gas outburst on blasting-working face by the method of gas peak-to-valley ratio", J. Chin. Coal Soc., 37(1), 104-108.
  13. Liu, C., Li, S., Xue, J. and Yu, G. (2016), "Identification method of high fractured body for overlying strata in goaf based on microseismic monitoring technology", J. Chin. U. Min. Technol., 45(4), 709-716.
  14. Ma, Y., Wang, E., Liu, Z., Chen, P. and Shi, X. (2012), "Attribute synthetic evaluation model for predicting risk of coal and gas outburst", J. Min. Safety Eng., 29(3), 416-420.
  15. Moulin, C., Largeron, C., Ducottet, C., Gery, M. and Barat, C. (2014), "Fisher linear discriminant analysis for text-image combination in multimedia information retrieval", Patt. Recogn., 47(1), 260-269. https://doi.org/10.1016/j.patcog.2013.06.003
  16. Rahman, M., Pk, M. and Uddin, M. (2015), "Optimum threshold parameter estimation of bidimensional empirical mode decomposition using fisher discriminant analysis for speckle noise reduction", Arab J. Info. Technol., 12(5), 456-464.
  17. Skoczylas, N. (2012), "Laboratory study of the phenomenon of methane and coal outburst", J. Rock. Mech. Min. Sci., 55, 102-107.
  18. Torano, J., Torno, S., Alvarez, E. and Riesgo, P. (2012), "Application of outburst risk indices in the underground coal mines by sublevel caving", J. Rock. Mech. Min. Sci., 50, 94-101. https://doi.org/10.1016/j.ijrmms.2012.01.005
  19. Wang, E., Li, Z., He, X. and Chen, L. (2014), "Application and pre-warning technology of coal and gas outburst by electromagnetic adiation", Coal Sci. Technol., 42(6), 53-57.
  20. Wang, Z., Ruan, Q. and An, G. (2015), "Face recognition using double sparse local fisher discriminant analysis", Math. Prob. Eng., 1-9.
  21. Wen, Z., Wang, X., Lin, Q., Lin, G., Chen, S. and Jiang, Y. (2016), "Simulatioin analysis on the strength and acoustic emission of jointed rock mass", Tehnicki Vjesnik-Tech. Gazette, 23(5), 1277-1284.
  22. Wen, Z., Wang, X., Tan, Y., Zhang, H. and Huang, W. (2016), "A study of rockburst hazard evaluation method in coal mine", Shock Vibr., 1-9.
  23. Wold, M.B., Connell, L.D. and Choi, S.K. (2008), "The role of spatial variability in coal seam parameters on gas outburst behaviour during coal mining", J. Coal Geol., 75(1), 1-14. https://doi.org/10.1016/j.coal.2008.01.006
  24. Xiao, F., Liu, G., Zhang, Z., Shen, Z., Zhang, F. and Wang, Y. (2016), "Acoustic emission characteristics and stress release rate of coal samples in different dynamic destruction time", J. Min. Sci. Technol., 26(6), 981-988. https://doi.org/10.1016/j.ijmst.2016.09.001
  25. Xu, T., Tang, C.A., Yang, T.H., Zhu, W.C. and Liu, J. (2006), "Numerical investigation of coal and gas outburst in underground collieries", J. Rock. Mech. Min. Sci., 43(6), 905-919. https://doi.org/10.1016/j.ijrmms.2006.01.001
  26. Xue, S., Yuan, L., Xie, J. and Wang, Y. (2014), "Advances in gas content based on outburst control technology in Huainan, China", J. Min. Sci. Technol., 24(3), 385-389. https://doi.org/10.1016/j.ijmst.2014.03.017
  27. Yang, S., Tang, J., Zhao, S. and Hua, F. (2010), "Early warning on coal and gas outburst with dynamic indexes of gas emission", Disas. Adv., 3(4), 403-406.
  28. Yang, Z. and Zhou, S. (2015), "Modeling and prediction of daily gas concentration variation at a mining face based on the elliptic orbit model: A case study", J. Min. Sci. Technol., 25(6), 1045-1052. https://doi.org/10.1016/j.ijmst.2015.09.025
  29. Yu, B., Su, C. and Wang, D. (2015), "Study of the features of outburst caused by rock cross-cut coal uncovering and the law of gas dilatation energy release", J. Min. Sci. Technol., 25(3), 453-458. https://doi.org/10.1016/j.ijmst.2015.03.020
  30. Zhou, F., Sun, Y., Li, H. and Yu, G. (2016), "Research on the theoretical model and engineering technology of the coal seam gas drainage hole sealing", J. Chin. U. Min. Technol., 45(3), 433-439.
  31. Zhang, R. and Ian, S.L. (2010), "The application of a coupled artificial neural network and fault tree analysis model to predict coal and gas outburst", J. Coal Geol., 84(2), 141-152. https://doi.org/10.1016/j.coal.2010.09.004
  32. Zhang, T., Ren, S., Li, S., Zhang, T. and Xu, H. (2009), "Application of the catastrophe progression method in predicting coal and gas outburst", Min. Sci. Technol., 19(4), 430-434. https://doi.org/10.1016/S1674-5264(09)60080-6

Cited by

  1. A New Method for Predicting Coal and Gas Outbursts vol.2020, pp.None, 2017, https://doi.org/10.1155/2020/8867476