Geomechanics and Engineering

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Development and application of a floor failure depth prediction system based on the WEKA platform

  • Lu, Yao (College of Energy and Mining Engineering, College of Safety and Environmental Engineering, Shandong University of Science and Technology) ;
  • Bai, Liyang (Lvliang University) ;
  • Chen, Juntao (College of Energy and Mining Engineering, College of Safety and Environmental Engineering, Shandong University of Science and Technology) ;
  • Tong, Weixin (College of Energy and Mining Engineering, College of Safety and Environmental Engineering, Shandong University of Science and Technology) ;
  • Jiang, Zhe (College of Energy and Mining Engineering, College of Safety and Environmental Engineering, Shandong University of Science and Technology)
  • Received : 2020.07.05
  • Accepted : 2020.09.07
  • Published : 2020.10.10
⟨ Previous Next ⟩

Abstract

In this paper, the WEKA platform was used to mine and analyze measured data of floor failure depth and a prediction system of floor failure depth was developed with Java. Based on the standardization and discretization of 35-set measured data of floor failure depth in China, the grey correlation degree analysis on five factors affecting the floor failure depth was carried out. The correlation order from big to small is: mining depth, working face length, floor failure resistance, mining thickness, dip angle of coal seams. Naive Bayes model, neural network model and decision tree model were used for learning and training, and the accuracy of the confusion matrix, detailed accuracy and node error rate were analyzed. Finally, artificial neural network was concluded to be the optimal model. Based on Java language, a prediction system of floor failure depth was developed. With the easy operation in the system, the prediction from measured data and error analyses were performed for nine sets of data. The results show that the WEKA prediction formula has the smallest relative error and the best prediction effect. Besides, the applicability of WEKA prediction formula was analyzed. The results show that WEKA prediction has a better applicability under the coal seam mining depth of 110 m~550 m, dip angle of coal seams of 0°~15° and working face length of 30 m~135 m.

Keywords

Acknowledgement

The research described in this paper was financially supported from the funding of the Taishan Scholar Talent Team Support Plan for Advantaged & Unique Discipline Areas and Key research and development plan of Shandong Province (2018GSF117018; 2018GSF120003; 2019GSF111024), Shandong Provincial Natural Science Foundation (ZR2019BEE013) and National Natural Science Foundation of China(51804179; 51604167; 51974173), State Key Laboratory of Mining Disaster Prevention and Control Co-founded by Shandong Province and the Ministry of Science and Technology(MDPC2016ZR01).

References

  1. Bai, L.Y., Zhao, J.H., Liu, Z.X. and Zhang, Z.X. (2017), "Depth prediction of floor damage based on data mining algorithm", Coal Eng., 49(6), 92-95. https://doi.org/10.11799/ce201706027.
  2. Blumling, P., Bernier, F., Lebon, P. and Martin, C.D. (2007), "The excavationdamaged zone in clay formations--time-dependent behaviour and influ-ence on performance assessment", Phys. Chem. Earth, 32(8-14), 588-599. https://doi.org/10.1016/j.pce.2006.04.034.
  3. Bukowski, P. (2011), "Water hazard assessment in active shafts in upper Silesian coal basin mines", Mine Water Environ., 30(4), 302-311. https://doi.org/10.1007/s10230-011-0148-2.
  4. Butron, C., Gustafson, G., Fransson, A. and Funehag, J. (2010), "Drip sealing oftunnels in hard rock: A new concept for the design and evaluation of permea-tion grouting", Tunn. Undergr. Sp. Tech., 25(2), 114-121. https://doi.org/10.1016/j.tust.2009.09.008.
  5. Camoes, A. and Martins, F.F. (2017), "Compressive strength prediction of CFRP confined concrete using data mining techniques", Comput. Concrete, 19(3), 233-241. http://doi.org/10.12989/cac.2017.19.3.233.
  6. Fernandez, G. and Moon, J. (2010), "Excavation-induced hydraulic conductivity reduction around a tunnel - Part 1: Guideline for estimate of ground water inflow rate", Tunn. Undergr. Sp. Tech., 25(5), 560-566. https://doi.org/10.1016/j.tust.2010.03.006.
  7. Genis, M., Akcin, H., Aydan, O. and Bacak, G. (2018), "Investigation of possible causes of sinkhole incident at the Zonguldak Coal Basin, Turkey", Geomech. Eng., 16(2), 177-185. http://doi.org/10.12989/gae.2018.16.2.177.
  8. Huang, Z., Jiang, Z., Tang, X., Wu, X., Guo, D. and Yue, Z. (2016), "In situ measurement of hydraulic properties of the fractured zone of coal mines", Rock Mech. Rock Eng., 49(2), 603-609. https://doi.org/10.1007/s00603-015-0741-y.
  9. Jiang, N., Wang, C., Pan, H., Yin, D. and Ma, J. (2020), "Modeling study on the influence of the strip filling mining sequence on mining-induced failure", Energy Sci. Eng., 8(6), 2239-2255. https://doi.org/10.1002/ese3.660.
  10. Jimenez, R., Anupol, J., Cajal, B. and Gervilla, E. (2018), "Data mining techniques for drug use research", Addictive Behaviors Reports, 8, 128-135. https://doi.org/10.1016/j.abrep.2018.09.005.
  11. Kaveh, A., Hamzeziabari, S.M. and Bakhshpoori, T. (2018), "Soft computing-based slope stability assessment: A comparative study". Geomech. Eng., 14(3), 257-269. http://doi.org/10.12989/gae.2018.14.3.257.
  12. Komurlu, E., Kesimal, A. and Hasanpour, R. (2015), "In situ horizontal stress effect on plastic zone around circular underground openings excavated in elastic zones", Geomech. Eng., 8(6), 783-799. https://doi.org/10.12989/gae.2015.8.6.783.
  13. Li, L.P., Lei, T., Li, S.C., Xu, Z.H., Xue, Y.G. and Shi, S.S. (2015), "Dynamic risk assessment of water inrush in tunnelling and software development", Geomech. Eng., 9(1), 57-81. https://doi.org/10.12989/gae.2015.9.1.057.
  14. Liu, Q., Chai, J., Chen, S., Zhang, D., Yuan, Q. and Wang, S. (2020), "Monitoring and correction of the stress in an anchor bolt based on pulse prepumped brillouin optical time domain analysis", Energy Sci. Eng., 1-13. https://doi.org/10.1002/ese3.644.
  15. Liu, S. and Lin, Y. (2010), Grey System: Theory and its Application, Springer-Verlag Berlin Heidelberg, 379-401.
  16. Narain, R., Golas, A. and Lin, M.C. (2010), "Free-flowing granular materials with two-way solid coupling", Proceedings of the International Conference on Computer Graphics and Interactive Techniques, Seoul, Korea, December.
  17. Polak, K., Rozkowski, K. and Czaja, P. (2016), "Causes and effects of uncontrolled water inrush into a decommissioned mine shaft", Mine Water Environ., 35(2), 128-135. https://doi.org/10.1007/s10230-015-0360-6.
  18. Sato, T., Kikuchi, T. and Sugihara, K. (2000), "In-situ experiments on anexcavation disturbed zone induced by mechanical excavation in Neogenesedimentary rock at Tono mine, central Japan", Develop. Geotech. Eng., 84, 105-116. https://doi.org/10.1016/S0165-1250(00)80010-3.
  19. Schafer, M. and Teschauer, I. (2001), "Numerical simulation of coupled fluid-solid problems", Comput. Meth. Appl. Mech. Eng., 190(28), 3645-3667. https://doi.org/10.1016/S0045-7825(00)00290-5.
  20. Si, L., Zhang, H., Wei, J., Li, B. and Han, H. (2021), "Modeling and experiment for effective diffusion coefficient of gas in water- saturated coal", Fuel, 284, 118887. https://doi.org/10.1016/j.fuel.2020.118887.
  21. Wang, C., Shen, B., Chen, J., Tong, W., Jiang, Z., Liu, Y. and Li, Y. (2020), "Compression characteristics of filling gangue and simulation of mining with gangue backfilling: An experimental investigation", Geomech. Eng., 20(6), 485-495. https://doi.org/10.12989/gae.2020.20.6.485.
  22. Wu, J., Li, S.C., Xu, Z.H., Pan, D.D. and He, S.J. (2018), "Flow characteristics after water inrush from the working face in karst tunneling", Geomech. Eng., 14(5), 407-419. https://doi.org/10.12989/gae.2018.14.5.407.
  23. Yuan, Y.C., Li, S.C., Zhang, Q.Q., Li, L.P., Shi, S.S. and Zhou, Z.Q. (2016), "Risk assessment of water inrush in karst tunnels based on a modified grey evaluation model: Sample as Shangjiawan Tunnel", Geomech. Eng., 11(4), 493-513. https://doi.org/10.12989/gae.2016.11.4.493.
  24. Zhang, B. and Meng, Z. (2019), "Experimental study on floor failure of coal mining above confined water", Arab. J. Geosci., 12(4), 114-123. https://doi.org/10.1007/s12517-019-4250-2.
  25. Zhang, G.H., Jiao, Y.Y., Ma, C.X., Wang, H., Chen, L.B. and Tang, Z.C. (2018), "Alteration characteristics of granite contact zone and treatment measures for inrush hazards during tunnel construction-A case study", Eng. Geol., 235, 64-80. https://doi.org/10.1016/j.enggeo.2018.01.022.
  26. Zhou, Z.Q., Li, S.C., Li, L.P., Shi, S.S. and Xu, Z.H. (2015), "An optimal classification method for risk assessment of water inrush in karst tunnels based on the grey system", Geomech. Eng., 8(5), 631-647. https://doi.org/10.12989/gae.2015.8.5.631.