Skip to main content

Forecasting of Methane Hazard State in the Exploitation Wall Using Neural-Fuzzy System

  • Conference paper
  • First Online:
Mechatronics 2017 - Ideas for Industrial Applications (MECHATRONICS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 934))

Included in the following conference series:

  • 711 Accesses

Abstract

In hard coal mines the series of natural hazards take place, one of the most dangerous are gaseous hazards. However, the most commonly occurring gaseous hazard is methane hazard. Methane is odorless and colorless, lighter than air organic gas, of which large quantities are emitted during an exploitation of hard coal. It is inflammable gas which with appropriate air concentration becomes a very dangerous explosive gas. In order to ensure safety of the staff, the critical concentration of this gas cannot be allowed to occur in mining atmosphere. Therefore, it is reasonable to apply mechatronic systems which task is to register current methane concentrations in mining atmosphere, also to develop analytical systems in order to forecast these concentrations. Application of advanced artificial intelligence systems provides opportunities for effective forecasting of methane concentrations in underground headings. This forecast is based on the registered measurement data and determined ventilated parameters. In the paper, an example of application of artificial intelligence methods to build an analyzing methane hazard model in the region of exploited wall was presented. The way of formation of neural-fuzzy system based on numerical data was described. Hybrid system was built to determine current level of methane hazard and forecast its future concentration in the region of longwall during normal mining operations. For determination of system parameters automatically, methods of knowledge recovery (based on fuzzy clustering of measured data) and adaptive learning algorithm of neural-fuzzy system were used. Developed tool gives a lot of opportunities for practical application.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Brodny, J., Tutak, M.: Analysis of methane emission into the atmosphere as a result of mining activity. In: 16th International Multidisciplinary Scientific GeoConference SGEM 2016, SGEM Vienna GREEN Extended Scientific Sessions, SGEM2016 Conference Proceedings, Book 4, vol. 3, pp. 83–90 (2016). https://doi.org/10.5593/sgem2016/hb43/s06

  2. Brodny, J., Tutak, M.: Determination of the zone endangered by methane explosion in goaf with caving of operating longwalls. In: 16th International Multidisciplinary Scientific GeoConference SGEM 2016, SGEM 2016 Conference Proceedings, Book 1, vol. 2, pp. 299–306 (2016). https://doi.org/10.5593/sgem2016/b12/s03.039

  3. Dokumentacja projektu europejskiego AVENTO (Zaawansowane narzędzia do kontroli wentylacji i emisji metanu), Instytut Technik Innowacyjnych EMAG, Katowice 2014–2015 (niepublikowana)

    Google Scholar 

  4. Dokumentacja ściany N-2 w pokładzie 404/2 w KWK Pniówek, Pawłowice (2013)

    Google Scholar 

  5. Felka, D.: Metody budowy inteligentnych modeli na bazie danych numerycznych. Monografia: Młodzi Innowacyjni. Innowacyjne rozwiązania z dziedzinie automatyki, robotyki i pomiarów, Wydawnictwo PIAP, Warszawa (2012)

    Google Scholar 

  6. Felka, D., Brodny, J.: Application of neural-fuzzy system in prediction of methane hazard. In: Intelligent Systems in Production Engineering and Maintenance – ISPEM 2017. Advances in Intelligent Systems and Computing, vol. 637, pp. 151–160. Springer, Cham (2018)

    Google Scholar 

  7. Fuzzy Logic Toolbox User’s Guide. Revised for Version 2.2.24 (Release 2016b), The MathWorks, Inc. (2016)

    Google Scholar 

  8. Jang, J.-S.R., Sun, C.-T., Mizutani, E.: Neuro-Fuzzy and Soft Computing. A Computational Approach to Learning and Machine Intelligence. Prentice-Hall, Upper Saddle River (1997)

    Book  Google Scholar 

  9. Krause, E., Łukowicz, K.: Zasady prowadzenia ścian w warunkach zagrożenia metanowego. Instrukcja nr 17 GIG, Katowice – Mikołów (2004)

    Google Scholar 

  10. Łęski, J.: Systemy neuronowo – rozmyte, Wydawnictwo Naukowo – Techniczne, Warszawa (2008)

    Google Scholar 

  11. Miśkiewicz, K., Wojaczek, A., Wojtas, P.: Systemy Dyspozytorskie kopalń podziemnych i ich integracja – Wybrane problemy. Monografia, Wydawnictwo Politechniki Śląskiej, Gliwice (2011)

    Google Scholar 

  12. Mrozek, B., Felka, D.: Inteligentny model wskaźnika zagrożenia pożarowego w kopalni węgla. PAR Pomiary Automatyka Robotyka 02, 540–545 (2012)

    Google Scholar 

  13. Mróz, J., Felka, D., Broja, A., Małachowski, M.: Devices for measuring ventilation parameters and methane concentration as well as concept of complex monitoring of methane hazard in longwall area. Min. – Inform. Autom. Electr. Eng. 01(529), 7–18 (2017)

    Google Scholar 

  14. Osowski, S.: Sieci neuronowe w ujęciu algorytmicznym. Wydawnictwo Naukowo-Techniczne, Warszawa (1996)

    Google Scholar 

  15. Pawiński, J., Roszkowski, J., Strzemiński, J.: Przewietrzanie kopalń. Śląskie Wydawnictwo Techniczne, Katowice (1995)

    Google Scholar 

  16. Roszczynialski, W., Trutwin, W., Wacławik, J.: Kopalniane pomiary wentylacyjne. Wydawnictwo Śląsk, Katowice (1999)

    Google Scholar 

  17. Tutak, M., Brodny, J.: Assessment of hydrodynamics of gas flow through homogeneous and heterogeneous porous rock media. In: 17th International Multidisciplinary Scientific GeoConference SGEM 2017, vol. 17, no. 14, pp. 539–546 (2017). https://doi.org/10.5593/sgem2017/14

  18. Tutak, M., Brodny, J.: Influence of auxiliary ventilation devices on a distribution of methane concentration at the crossing of longwall and ventilation roadway. In: 17th International Multidisciplinary Scientific Geoconference SGEM (2017), vol. 17, no. 13, pp. 437–444 (2017). https://doi.org/10.5593/sgem2017/13

  19. Tutak, M., Brodny, J.: Analysis of influence of goaf sealing from tailgate on the methane concentration at the outlet from the longwall. In: IOP Conference Series: Earth and Environmental Science, vol. 95, p. 042025 (2017). https://doi.org/10.1088/1755-1315/95/4/042025

  20. Tutak, M., Brodny, J.: Determination of particular endogenous fires hazard zones in goaf with caving of longwall. In: IOP Conference Series: Earth and Environmental Science, vol. 95, p. 042026 (2017). https://doi.org/10.1088/1755-1315/95/4/042026

  21. Tutak, M.: Analysis of varying levels of methane emissions from coal mines in Poland. In: SGEM 2017 Vienna GREEN Conference Proceedings, vol. 17, no. 43, pp. 301–308 (2017). https://doi.org/10.5593/sgem2017h/43/s19.038

  22. Tutak, M.: Assessment of hydrodynamics of gas flow through the porous rock structures. In: 17th International Multidisciplinary Scientific GeoConference SGEM 2017, SGEM2017 Vienna GREEN Conference Proceedings, vol. 17, no. 15, pp. 53–60 (2017). https://doi.org/10.5593/sgem2017h/15/s06.007

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dariusz Felka .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Felka, D., Brodny, J. (2019). Forecasting of Methane Hazard State in the Exploitation Wall Using Neural-Fuzzy System. In: Świder, J., Kciuk, S., Trojnacki, M. (eds) Mechatronics 2017 - Ideas for Industrial Applications. MECHATRONICS 2017. Advances in Intelligent Systems and Computing, vol 934. Springer, Cham. https://doi.org/10.1007/978-3-030-15857-6_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-15857-6_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-15856-9

  • Online ISBN: 978-3-030-15857-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics