Geomechanics and Engineering

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Application of black box model for height prediction of the fractured zone in coal mining

  • Zhang, Shichuan (College of Mining and Safety Engineering, Shandong University of Science and Technology) ;
  • Li, Yangyang (College of Mining and Safety Engineering, Shandong University of Science and Technology) ;
  • Xu, Cuicui (College of Mining and Safety Engineering, Shandong University of Science and Technology)
  • Received : 2016.10.15
  • Accepted : 2017.06.19
  • Published : 2017.12.25
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Abstract

The black box model is a relatively new option for nonlinear dynamic system identification. It can be used for prediction problems just based on analyzing the input and output data without considering the changes of the internal structure. In this paper, a black box model was presented to solve unconstrained overlying strata movement problems in coal mine production. Based on the black box theory, the overlying strata regional system was viewed as a "black box", and the black box model on overburden strata movement was established. Then, the rock mechanical properties and the mining thickness and mined-out section area were selected as the subject and object respectively, and the influences of coal mining on the overburden regional system were discussed. Finally, a corrected method for height prediction of the fractured zone was obtained. According to actual mine geological conditions, the measured geological data were introduced into the black box model of overlying strata movement for height calculation, and the fractured zone height was determined as 40.36 m, which was comparable to the actual height value (43.91 m) of the fractured zone detected by Double-block Leak Hunting in Drill. By comparing the calculation result and actual surface subsidence value, it can be concluded that the proposed model is adaptable for height prediction of the fractured zone.

Keywords

Acknowledgement

Supported by : Natural Science Foundation of Shandong Province, Shandong University of Science and Technology

References

  1. Azman, K. and Kocijan, J. (2007), "Application of Gaussian processes for black-box modelling of biosystems", Isa T., 46(4), 443-457. https://doi.org/10.1016/j.isatra.2007.04.001
  2. Bahrami, S. and Ardejani, F.D. (2016), "Prediction of pyrite oxidation in a coal washing waste pile using a hybrid method, coupling artificial neural networks and simulated annealing (ANN/SA)", J. Clean. Prod., 137, 1129-1137. https://doi.org/10.1016/j.jclepro.2016.08.005
  3. BP PLC Statistical Review of World Energy 2014 in Moscow-Final. Fair Disclosure Wire (Quarterly Earnings Reports), Regional Business News, Ipswich, Massachusetts, U.S.A.
  4. Chung, Y. and Chang, I. (2015), "How accurate is accident data in road safety research? An application of vehicle black box data regarding pedestrian-to-taxi accidents in Korea", Accident Anal. Prevent., 84, 1-8. https://doi.org/10.1016/j.aap.2015.08.001
  5. Farina, M. and Piroddi, L. (2009), "Simulation error minimization-based identification of polynomial input-output recursive emodels", Proceedings of the 15th IFAC Symposium on System Identification, Saint-Malo, France, July.
  6. Farina, M. and Piroddi, L. (2010a), "An iterative algorithm for simulation error based identification of polynomial input-output models using multi-step prediction", J. Contr., 83(7), 1442-1456. https://doi.org/10.1080/00207171003793262
  7. Farina, M. and Piroddi, L. (2010b), "Identification of polynomial input-output recursive models with simulation error minimization methods", J. Syst. Sci., 43(2), 319-333.
  8. Fiscor, S. (2016), "U.S. longwall operators scale back production", Coal Age, 121(2), 18-22.
  9. Ghabraie, B., Ren, G., Zhang, X. and Smith, J. (2015), "Physical modelling of subsidence from sequential extraction of partially overlapping longwall panels and study of substrata movement characteristics", J. Coal Geol., 140, 71-83. https://doi.org/10.1016/j.coal.2015.01.004
  10. Gu, P. (2001), "Application of black-box theory in traditional Chinese medicine", J. Nanjing TCM U., 2(2), 66-68.
  11. Johansen, T.A., Shorten, R., Murray-Smith, R. (2000), "On the interpretation and identification of dynamic Takagi-Sugeno fuzzy models", IEEE T. Fuzz. Syst., 8(3), 297-313. https://doi.org/10.1109/91.855918
  12. Liu, G., Buckley, S.M., Ding, X., Chen, Q. and Luo, X. (2009), "Estimating spatiotemporal ground deformation with improved persistent-scatterer radar interferometry", IEEE T. Geosci. Remot., 47(9), 3209-3219. https://doi.org/10.1109/TGRS.2009.2028797
  13. Murray-Smith, R., Johansen, T.A. and Shorten, R. (1999), "On transient dynamics, off-equilibrium behaviour and identification in blended multiple model structures", Proceedings of the European Control Conference, Karlsruhe, Germany, August-September.
  14. Nax, H.H., Burton-Chellew, M.N., West, S.A. and Young, H.P. (2013), "Learning in a black box", J. Econ. Behav. Org., 127(3), 1-15.
  15. Rogstad, E., Briand, L. and Torkar, R. (2013), "Test case selection for black-box regression testing of database applications", Info. Software Technol., 55(10), 1781-1795. https://doi.org/10.1016/j.infsof.2013.04.004
  16. Storch, T. (2016), "Black-box complexity: Advantages of memory usage", Info. Process. Lett., 116(6), 428-432. https://doi.org/10.1016/j.ipl.2016.01.009
  17. Sun, C., Ai, L. and Wu, Z. (2008), "The new black box theory and its application", Sci. Technol. Info., 34, 57-60.
  18. Sun, X. and Huang, D. (2014), "An explosive growth of wind power in China", J. Green Energy., 11(8), 849-860. https://doi.org/10.1080/15435075.2013.830261
  19. Xia, B., Gao, S. and Chen, D. (2003), "Chinese velocity of money and economic fluctuations effectiveness china monetary policy from the perspective of black box theory", J. Fin. Res., 12, 1-18.
  20. Xu, J., Wang, X., Liu, W. and Wang, Z. (2009), "Effects of primary keystratum location on height of water flowing fracture zone", Chin. J. Rock Mech. Eng., 28(2), 380-385.
  21. Zhang, X. (1999), "Study on the distribution of blackbox theory model optimization of environmental monitoring", Environ. Eng., 17(3), 56-57.
  22. Zhang, X., Fan, X. and Zhao, D. (2002), "Temporal and spatial processes of overlying strata movement", Chin. J. Rock Mech. Eng., 21(1), 56-59.

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