Skip to main content
Log in

A Virtual Reality Collaborative Planning Simulator and Its Method for Three Machines in a Fully Mechanized Coal Mining Face

  • Research Article - Mechanical Engineering
  • Published:
Arabian Journal for Science and Engineering Aims and scope Submit manuscript

Abstract

The existing automatic control program and its parameters for three machines in a fully mechanized Coal Mining face are static and simplex and are therefore inadequate for satisfying the complex and dynamic environment of underground coal mines. To overcome this problem, a collaborative mathematical model is established that includes the effects of a dynamic environment. A virtual reality collaborative planning simulator with methods for the three machines is also proposed based on a multi-agent system. According to the dynamic characteristics of the environment, equipment, and technologies, a fully mechanized Unity3D simulator (FMUnitySim) is designed in terms of multiple factors and multiple dimensions. The factors affecting the coordinated operation of the three machines are analyzed and modeled. The communication modes, coordination, and redundant sensing process among multiple agents, which include the shearer agent and the scraper conveyor agent, are also investigated in detail. Using this system, the key parameters of the three machines can be planned and adjusted online to design and distinctly observe the corresponding collaborative simulations of coordinated operation with multiple perspectives and in real time. Tests of different maximum shearer haulage speeds for regular or reverse transporting coal are designed; their key parameters, including the average shearer haulage speed, average follower distance, and average scraper conveyor load, are planned and simulated using FMUnitySim. The optimal parameter combination is obtained by analyzing and comparing the simulation results. The proposed FMUnitySim offers an effective means and theoretical basis for the rapid planning and safe automatic production of a fully mechanized Coal Mining face.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Abbreviations

\(A_\mathrm{area}\) :

Maximum cross-sectional area to transport coal for the scraper conveyor

A(t):

Cross-sectional area to transport coal for the scraper conveyor at moment t

\(B_\mathrm{normal} \) :

Critical value of the roof broken degree

\(B_{zj} (i)\) :

Corresponding roof broken degree of hydraulic support No. i

\(D_\mathrm{drum}\) :

Drum diameter of the shearer

\(D_\mathrm{follow}\) :

Follower distance

\(D_\mathrm{zbc}\) :

Middle trough width of the scraper conveyor

\(f_{1}\) :

Running resistance coefficient of the scraper chain

\(f_{2}\) :

Running resistance coefficient of coal

\(f(S_r (t))\) :

Cutting height of the rear drum at the position of \(S_{r}(t)\)

\(H_{c}\) :

Machine height of the shearer

\(H_\mathrm{down}\) :

Length of the retracting columns

\(H_\mathrm{rise}\) :

Length of the rising columns

\(H_{u}(i)\) :

Corresponding mine height of middle trough No. i

\(H_{zj} (m)\) :

Height of hydraulic support No. m

\(I_\mathrm{motor}\) :

Virtual electric current of the virtual shearer

J :

Cutting depth of the shearer

\(K_{g}\) :

Capacity decline coefficient of the scarper conveyor due to poor operating conditions

L :

Length of the working face (m)

l :

Distance of the cutting position and unloading position

\(L_\mathrm{gbj}\) :

Running distance of the shearer from moment \(t_{1 }\) to moment \(t_{2}\)

\(L_\mathrm{JiTou}\) :

Distance from the front drum to the unloading point of the shearer

\(L_\mathrm{JiShen}\) :

Distance from the left drum hinge point to the right drum hinge point for the shearer

\(L_\mathrm{wan}\) :

Distance from the start point of the shearer to the coal seam

\(L_{y}\) :

Length of the shearer rocker arm

\(m_\mathrm{front} (t)\) :

Cutting amount of the front drum from the beginning to moment t

\(m_{\text{ Ins-front }} (t)\) :

Instantaneous coal cutting amount of the front drum at moment t

\(m_{\text{ Ins-rear }} (t)\) :

Instantaneous coal cutting amount of the rear drum at moment t

\(m_{\text { Ins-transport}} (t)\) :

Instantaneous amount of shipped coal

\(m_\mathrm{rear} (t)\) :

Coal cutting amount of the rear drum from the beginning to moment t

\(m_{\text {total-transport}} (t)\) :

Total cutting amount of the shearer from the beginning to moment t

\(m_\mathrm{sudd}\) :

Mutation load of the scraper conveyor caused by the collapse of the coal wall

N :

Serial number of the advancing hydraulic support

\(n_\mathrm{broken} \) :

Influence parameter of the broken roof

\(n_\mathrm{condition} \) :

Influence parameter of the equipment working condition

\(n_\mathrm{hy} \) :

Influence parameter of the action mode

\(n_\mathrm{press} \) :

Influence parameter of the mine pressure

\(N_\mathrm{motor}\) :

Motor load of the scraper conveyor

\(P_\mathrm{normal} \) :

Critical value of the roof pressure for the hydraulic support

\(P_{zj} (i)\) :

Corresponding roof pressure value of hydraulic support No. i

\(Q_\mathrm{permit} \) :

Maximum permitted power of transporting coal

\(q_{0}\) :

Scraper chain weight per meter (kg/m)

q(t):

Mine stream amount of the current middle trough per meter

Q(t):

Total load of the scraper conveyor from the beginning to moment t

\(Q_\mathrm{Ins} (t)\) :

Scraper conveyor load at moment t

S(t):

Shearer fuselage position at moment t

\(S_{f}(t)\) :

Front drum position at moment t

\(S_{r}(t)\) :

Rear drum position at moment t

\(S_{zj} (m)\) :

Position of hydraulic support No. m

\(S_\mathrm{tuiyi} (m)\) :

Elongation length of the advancing units for hydraulic support No. m

\(S_{r-l} \) :

Action area of the columns

\(S_{d-l} \) :

Action area of the advancing units

\(\mathrm{state}(m)\) :

State of hydraulic support No. m

\(t_{0}\) :

Running start moment of the shearer

\(t_{1}\) :

Moment when the front drum begins to cut coal

\(t_{2}\) :

Moment when the scraper conveyor begins to transport coal shipped out

\(t_{3}\) :

Moment when the rear drum begins to cut coal

\(t_{\text{ norm-move }} \) :

Action time of the hydraulic support

\(V_{o}\) :

Relative speed from \(V_{c }\) to \(V_{g}\)

\(V_{g}\) :

Scraper conveyor chain speed

\(V_{c}\) :

Shearer haulage speed

\(V_{y}\) :

Advancing speed of the hydraulic support

YiJiaFangShi:

Current advancing mode of the hydraulic support

X(i):

Corresponding X coordinate of middle trough No. i

\(\eta \) :

Transmission mechanism efficiency of the scraper conveyor

\(\beta \) :

Dip degree of the coal seam (degrees)

\(\alpha _{S(t)} \) :

Relative angle of the front drum to the fuselage at the position of S(t)

\(\alpha _{{r S(t)}} \) :

Relative angle of the rear drum to the fuselage at the position of S(t)

\(\rho _{\mathrm{soild}} \) :

Density of solid coal

\(\rho _{\mathrm{dispersion}} \) :

Density of bulk coal

\(\lambda \) :

Divisor of (Sr(t)- Sr(t3))/Dzbc

\(\sigma \) :

Remainder of (Sr(t)- Sr(t3)) %Dzbc

\(\phi (m)\) :

Flap angle of hydraulic support No. m

References

  1. Wang, J.H.; Wang, Y.H.; Fu, J.H.: Crucial technology research and demonstration of digital mines. J. China Coal. Soc. 41(6), 1323–1331 (2016)

    Google Scholar 

  2. Ge, S.R.: Key technology of intelligent coal mining equipment. Coal Sci. Technol. 42(9), 7–11 (2014)

    Google Scholar 

  3. Niu, J.F.: Key Study on automatic and intelligent following control system of hydraulic powered support in fully-mechanized coal mining face. Coal Sci. Technol. 43(12), 85–91 (2015)

    Google Scholar 

  4. Wang, C.; Tu, S.; Chen, M.: Optimal selection of a longwall mining method for a thin coal seam working face. Arab. J. Sci. Eng. 41(9), 1–11 (2016)

    Google Scholar 

  5. Wang, J.H.; Huang, L.T.; Li, S.B.: Development of intelligent technology and equipment in fully-mechanized coal mining face. J. China Coal Soc. 39(8), 1418–1423 (2014)

    Google Scholar 

  6. Fan, Q.G.; Li, W.: Study on equipment positioning and task coordination for three machines controlling on the mechanized mining face. China J. Mech. Eng. 9, 73–73 (2015)

    Google Scholar 

  7. Opensim, J.: A 3D Simulator for autonomous robots. http://opensimulator.sourceforge.net/ (2008). Accessed 14 April 2017

  8. Freese, M.; Singh, S.; Ozaki, F.: Virtual robot experimentation platform v-rep: a versatile 3D robot simulator. In: Ando, N., Balakirsky, S., Hemker, T., Reggiani, M., von Stryk, O. (eds.) Simulation. Modeling, and Programming for Autonomous Robots, pp. 51–62. Springer, Berlin, Heidelberg (2010)

  9. Mcdowell, P.; Darken, R.; Sullivan, J.: Delta3D: a complete open source game and simulation engine for building military training systems. J. Def. Model. Simul. 3(3), 143–154 (2006)

    Article  Google Scholar 

  10. Lewis, M.; Wang, J.; Hughes, S.: USARSim: simulation for the study of human–robot interaction. J. Cognit. Eng. Decis. Mak. 1(1), 98–120 (2007)

    Article  Google Scholar 

  11. Koenig, N.; Howard, A.: Design and use paradigms for gazebo, an open-source multi-robot simulator. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, 28 September–2 October, vol. 3, pp. 2149–2154. Sendai (2004)

  12. Lee, W.; Cho, S.; Chu, P.: Automatic agent generation for IoT-based smart house simulator. Neurocomputing 209, 14–24 (2016)

    Article  Google Scholar 

  13. Becker-Asano, C.: A multi-agent system based on unity 4 for virtual perception and wayfinding. Transp. Res. Procedia 2, 452–455 (2015)

    Article  Google Scholar 

  14. Meng, W.: ROSUnitySim: development and experimentation of a real-time simulator for Multi-UAV local planning. Simulation 92(10), 002562–002567 (2016)

    Google Scholar 

  15. Meng, Wei.: ROS+unity: An efficient high-fidelity 3D multi-UAV navigation and control simulator in GPS-denied environments. In: Conference of the IEEE Industrial Electronics Society IEEE, pp. 002562–002567 (2015)

  16. Xu, Z.; Lu, X.Z.; Guan, H.: A virtual reality based fire training simulator with smoke hazard assessment capacity. Adv. Eng. Softw. 68(2), 1–8 (2014)

    Article  Google Scholar 

  17. Cha, M.; Han, S.; Lee, J.: A virtual reality based fire training simulator integrated with fire dynamics data. Fire Saf. J. 50(3), 12–24 (2012)

    Article  Google Scholar 

  18. Manca, D.; Brambilla, S.; Colombo, S.: Bridging between Virtual Reality and accident simulation for training of process-industry operators. Adv. Eng. Softw. 55(1), 1–9 (2013)

    Article  Google Scholar 

  19. Kizil, M.S.: Virtual reality applications in Australian minerals industry. J. S. Afr. I. Min. Metall. 31, 569–574 (2013)

    Google Scholar 

  20. Tichon, J.; Burgess-limerick, R.: A review of virtual reality as a medium for safety related training in mining. J. Health Saf. Res. Pract. 3(1), 33–40 (2011)

    Google Scholar 

  21. Perez, P.; Pedram, S.; Dowcet, B.: Impact of virtual training on safety and productivity in the mining industry. In: Conference: MODSIM 2013, Adelaid (2013)

  22. Pedram, S.; Perez, P.; Dowsett, B.: Assessing the impact of virtual reality-based training on health and safety issues in the mining industry. In: ISNGI2013—International Symposium for Next Generation Infrastructure (2013)

  23. Pedram, S.; Perez, P; Palmisano, S.: Evaluating the influence of virtual reality-based training on workers’ competencies in the mining industry. In: Bruzzone, A.G., De Felice, F., Massei, M., Merkuryev, Y., Solis, A., Zacharewicz, G. (eds.) 13th International Conference on Modeling and Applied Simulation, MAS 2014, pp. 60–64. Curran, Red Hook (2014)

  24. Pedram, S., Perez, P.; Palmisano, S.: Evaluating 360-Virtual Reality for Mining Industry’s Safety Training, International Conference on Human–Computer Interaction, pp. 555–561. Springer, Cham (2017)

  25. Kerridge, A.P.; Kizil, M.S.; Howarth, D.F.: Use of virtual reality in mining education. The AusIMM Young Leader’s Conference, pp. 1–5. The Australasian Institute of Mining and Metallurgy (2003)

  26. Grabowski, A.; Jankowski, J.: Virtual reality-based pilot training for underground coal miners. J. Saf. Sci. 72, 310–314 (2015)

    Article  Google Scholar 

  27. Foster, P.; Burton, A.: Virtual reality in improving mining ergonomics. J. S. Afr. I. Min. Metall. 104(2), 129–133 (2004)

    Google Scholar 

  28. Stothard, P.; Laurence, D.: Application of a large-screen immersive visualization system to demonstrate sustainable mining practices principles. Trans. I. Min Metall. 23, 199–206 (2014)

    Google Scholar 

  29. Stothard, P.: The feasibility of applying virtual reality simulation to the coal mining operations. Aust. J. Min. Metall. Publ. Ser. 5, 175–183 (2003)

    Google Scholar 

  30. Foster, P.J.; Burton, A.: Modelling potential sightline improvements to underground mining vehicles using virtual reality. Trans. J. Min. Metall. 115, 85–90 (2013)

    Google Scholar 

  31. Zhang, S.X.: Augmented reality on longwall face for unmanned mining. Appl. Mech. Mater. 40–41(6), 388–391 (2010)

    Article  Google Scholar 

  32. Akkoyun, O.; Careddu, N.: Mine simulation for educational purposes: a case study. Comput. Appl. Eng. Educ. 23(2), 286–293 (2015)

    Article  Google Scholar 

  33. Kijonka, M.; Kodym, O.; Coal industry technologies simulation with virtual reality utilization. In: Proceedings of the 13th International Carpathian Control Conference (ICCC), High Tatras, IEEE, pp. 278–283 (2012)

  34. Zhang, X.; An, W.; Li, J.: Design and application of virtual reality system in fully mechanized mining face. Procedia Eng. 26(4), 2165–2172 (2011)

    Google Scholar 

  35. Wan, L.R.; Gao, L.; Liu, Z.H.: The application of virtual reality technology in mechanized mining face. Adv. Intell. Syst. Comput. 181, 1055–1061 (2013)

    Google Scholar 

  36. Torano, J.; Diego, I.; Menéndez, M.: A finite element method (FEM)—fuzzy logic (soft computing)—virtual reality model approach in a coalface longwall mining simulation. Autom. Constr. 17(4), 413–424 (2008)

    Article  Google Scholar 

  37. Sun, H.B.; Tan, C.; Yao, X.G.: Research on three-dimension scene modeling technology of 3DVR platform for shearer. J. China Univ. Min. Technol. 39(5), 676–681 (2010)

    Google Scholar 

  38. Xie, J.C.; Yang, Z.J.; Wang, X.W.: Design and key technologies of virtual assembly and simulation of mining, driving and transporting equipment system. J. Syst. Simul. 27(4), 794–802 (2015)

    Google Scholar 

  39. Li, A.L.; Zheng, X.W.; Wang, W.: Virtual motion simulation of hydraulic support based on unity 3D. In: First International Conference on Information Sciences, Machinery, Materials and Energy. Atlantis Press (2015)

  40. Stothard, P.; Squelch, A.; Stone, R.: Taxonomy of interactive computer-based visualization systems and content for the mining industry—part 2. In: International Future Mining Conference and Exhibition, vol. 124, no. 2, pp. 201–210. OAI (2015)

  41. Li, W.N.: Fully Mechanized Three-Machine Linkage Process Simulation Based on Virtual Reality Technology. Dissertation Xi‘an: Xi‘an University of Science and Technology (2014)

  42. Xu, X.Z.; Meng, X.R.; He, Y.R.: Research on virtual simulation of full mechanized mining face production based on three-dimensional visualization and virtual simulation. J. Saf. Sci. Technol. 1, 26–32 (2014)

    Google Scholar 

  43. Tang, S.S.; Wei, C.K.: Design of monitoring system for hydraulic support based on LabVIEW. J. Adv. Mater. Res. 989–994, 2758–2760 (2014)

    Article  Google Scholar 

  44. Lo, J.Z.; Chen, H.Z.; Sui, G.: Study on simulation system of fully mechanized mining face based on virtual reality. J. Syst. Simul. 19(18), 4164–4167 (2007)

    Google Scholar 

  45. Li, H.; Chen, K.; Zhang, X.: Disign of monitoring and control system based on virtual reality technology on fully-mechanized coal mining face. Ind. Min. Autom. 42(4), 15–18 (2016)

    Google Scholar 

  46. Liang, S.; Chen, Y.; Zheng, X.: Study of monitoring system of hydraulic support movement state based on virtual reality. In: International Conference on Mechatronic Sciences, Electric Engineering and Computer, pp. 3434–3437 (2013)

  47. Yan, H.F.; Su, F.X.; Chen, Z.H.; A study on the remote monitoring system of hydraulic support based on 3DVR. In: Audio Language and Image Processing (ICALIP), 2010 International Conference on. IEEE, pp. 912–915 (2010)

  48. Wand, Y.: Design Manual for Continuous Conveying Machinery. China Railway Publishing House, Beijing (2001)

    Google Scholar 

Download references

Acknowledgements

This work is supported by Shanxi Postgraduate Education Innovation Project (No. 2017BY046), Shanxi Scholarship Council of China (No. 2016-043), Program for the Outstanding Innovative Teams of Higher Learning Institutions of Shanxi (No. 2014), Shanxi Province Scholars Scientific and Technological Activities Preferred Funding Project (No. 2016) and Applied Basic Research Project of Shanxi (No. 201601D011050).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zhaojian Yang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xie, J., Yang, Z., Wang, X. et al. A Virtual Reality Collaborative Planning Simulator and Its Method for Three Machines in a Fully Mechanized Coal Mining Face. Arab J Sci Eng 43, 4835–4854 (2018). https://doi.org/10.1007/s13369-018-3164-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13369-018-3164-8

Keywords

Navigation