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Fuzzy logic-based determination of ventilation parameters in active mining areas

The airflow rate in active mining areas is determined from the direct measurement of air quality parameters at the specific moment of time. This conventional approach to calculation of air volume required for mine ventilation features the indirectness of air quality evaluation on the assumption of the most unfavorable situation upon condition of simultaneous activity in all operating zones, which results in excessive airing and, as a consequence, in extra operating expenditures. The automated ventilation control enables flexible adjustment of mine air volume and airflow distribution as consistent with the current needs per mining areas, while the instrumentation for the continuous measurement of air temperature and gas concentration allows determining appropriate ventilation parameters for the air quality to meet the safety standards. The fuzzy logic application to evaluation of the current air quality ensures well-balanced mine ventilation in terms of safety and energy efficiency, owing to ranging the air quality criteria as consistent with regulatory documents. The mine testing data on ventilation monitoring in an active mining zone of Belaruskali’s Mine 4 using automated airflow control facilities demonstrate that the proposed approach to the required air volume calculation effectively provides the routine ventilation mode and ensures a real-time response to gas concentration build-up in mine air to prevent accidents in active mining zones in advance.

Keywords: air volume calculation, automated ventilation control, methane, fuzzy logic, airing controller, longwall, fan, gas concentration, energy efficiency.
For citation:

Kashnikov A. V., Kruglov Yu. V. Fuzzy logic-based determination of ventilation parameters in active mining areas. MIAB. Mining Inf. Anal. Bull. 2023;(5):68-82. [In Russ]. DOI: 10.25018/0236_1493_2023_5_0_68.

Acknowledgements:

The study was supported by the Ministry of Science and Higher Education of the Russian Federation under State Contract No. 075-03-2021-374 dated 29 December 2020, Registration Number 1021062110595-3-1.5.7.

Issue number: 5
Year: 2023
Page number: 68-82
ISBN: 0236-1493
UDK: 622.45
DOI: 10.25018/0236_1493_2023_5_0_68
Article receipt date: 29.09.2022
Date of review receipt: 06.03.2023
Date of the editorial board′s decision on the article′s publishing: 10.04.2023
About authors:

A.V. Kashnikov1, Junior Researcher, e-mail: alexey.kashnikov@gmail.com, ORCID ID: 0000-0002-3872-5862,
Yu.V. Kruglov1, Dr. Sci. (Eng.), Head of Project and Innovation Center, e-mail: aerolog@list.ru, ORCID ID: 0000-0003-0977-7484,
1 Mining Institute of Ural Branch, Russian Academy of Sciences, 614007, Perm, Russia.

 

For contacts:

A.V. Kashnikov, e-mail: alexey.kashnikov@gmail.com.

Bibliography:

1. Hardcastle S., Kocsis C., Lacroix R. Strategic mine ventilation control: a source of potential energy savings. Proceedings of Montreal Energy & Mines. Montreal, Canada. 2007, pp. 255—263.

2. Hardcastle S., Kocsis C., Li G. Analyzing ventilation requirements and the utilization efficiency of the Kidd Creek mine ventilation system. 12th U.S.-North American Mine Ventilation Symposium. Reno, NV, USA. 2008, pp. 27—36.

3. Semin M. A., Grishin E. L., Levin L. Yu., Zaitsev A. V. Automated ventilation control in mines. Challenges, state of the art, areas for improvement. Journal of Mining Institute. 2020, vol. 246, pp. 623—632. [In Russ]. DOI: 10.31897/PMI.2020.6.4.

4. Moreau K., Laamanen C., Bose R., Shang H., Scott J. A. Environmental impact improvements due to introducing automation into underground copper mines. International Journal of Mining Science and Technology. 2021, vol. 31, no. 6, pp. 1159—1167. DOI: 10.1016/j.ijmst.2021.11.009.

5. Semin M. A., Levin L. Y., Maltsev S. V. Development of automated mine ventilation control systems for belarusian potash mines. Archives of Mining Sciences. 2020, vol. 65, no. 4, pp. 803—820. DOI: 10.24425/ams.2020.135178.

6. Acuña E., Lowndes I. A review of primary mine ventilation system optimization. Interfaces. 2014, vol. 44, no. 2, pp. 163—175. DOI: 10.1287/inte.2014.0736.

7. Chatterjee A., Zhang L., Xia X. Optimization of mine ventilation fan speeds according to ventilation on demand and time of use tariff. Applied Energy. 2015, vol. 146, pp. 65—73. DOI: 10.1016/j.apenergy.2015.01.134.

8. Acuña E., Allen C. Ventilation control system implementation and energy consumption reduction at Totten Mine with Level 4 Tagging and future plans. Proceedings of the First International Conference on Underground Mining Technology. Sudbury, Canada. 2017, pp. 89—95. DOI: 10.36487/ACG_rep/1710_06_Acuna.

9. Acuña E., Feliú A. Considering ventilation on demand for the developments of the New Level Mine Project, El Teniente. A Deep Mining 2014: Proceedings of the Seventh International Conference on Deep and High Stress Mining. Australian Centre for Geomechanics, Perth, Australia. 2014, pp. 813—821. DOI: 10.36487/ACG_rep/1410_59_Acuna.

10. De Vilhena C. L., Margarida da Silva J. Cost-saving electrical energy consumption in underground ventilation by the use of ventilation on demand. Mining Technology. 2019, vol. 129, no. 1, pp. 1—8. DOI: 10.1080/25726668.2019.1651581.

11. Levin L. Y., Semin M. A. Conception of automated mine ventilation control system and its implementation on Belarussian potash mines. Proceedings of the 16th North American Mine Ventilation Symposium. Colorado, USA. 2017, pp. 17.1—17.8.

12. Grishin E. L., Nakaryakov E. V., Trushkova N. A., Sanikovich A. N. Experience in implementation of dynamic mine ventilation control. Gornyi Zhurnal. 2018, no. 8, pp. 103—108. [In Russ]. DOI: 10.17580/gzh.2018.08.15.

13. Kashnikov A. V., Levin L. Y. Applying machine learning techniques to mine ventilation control systems. XX Mezhdunarodnaya konferentsiya po myagkim vychisleniyam i izmereniyam (SCM-2017). Sbornik dokladov. T. 1 [XX International Conference on Soft Computing and Measurements (SCM-2017). Collection of reports. Vol. 1], Saint-Petersburg, SPbGETU «LETI», 2017, pp. 553—556. [In Russ].

14. Kashnikov A. V., Kruglov Yu. V. Estimating energy consumption of mine fans in underground mines in case of uncertainty of fan influence zones. Fiziko-tekhnicheskie problemy razrabotki poleznykh iskopaemykh. 2022, no. 4, pp. 72—84. [In Russ]. DOI: 10.15372/FTPRPI 20220408.

15. Maltsev S. V., Kazakov B. P., Semin M. A. Efficiency upgrading techniques for complex mine ventilation systems. News of the Tula state university. Sciences of Earth. 2019, no. 4, pp. 283—291. [In Russ].

16. Hameed I. A. Simplified architecture of a type-2 fuzzy controller using four embedded type-1 fuzzy controllers and its application to a greenhouse climate control system. Proceedings of the Institution of Mechanical Engineers Part I: Journal of Systems and Control Engineering. 2019, vol. 223, no. 5, pp. 619—631. DOI: 10.1243/09596518JSCE708.

17. Saritas I., Etik N., Allahverdi N., Sert I. Fuzzy expert system design for operating room air-condition control systems. Expert Systems with Applications. 2007, vol. 36, no. 6, pp. 23—30. DOI: 10.1016/j.eswa.2009.02.028.

18. Fashilenko V. N., Varfolomeev S. V. Sypply-extract ventilation electric drives system control in concentration mill. MIAB. Mining Inf. Anal. Bull. 2015, no. 2, pp. 182—188. [In Russ].

19. Kashnikov A. V., Levin L. Yu. Fan and regulators fuzzy control in mine ventilation systems. XXII Mezhdunarodnaya konferentsiya po myagkim vychisleniyam i izmereniyam (SCM-2019). Sbornik dokladov [XXII International Conference on Soft Computing and Measurements (SCM2019). Collection of reports], Saint-Petersburg, SPbGETU «LETI», 2019, pp. 128—131. [In Russ].

20. Izquierdo S., Izquierdo L. Mamdani fuzzy systems for modelling and simulation: A critical assessment. Journal of Artificial Societies and Social Simulation. 2018, vol. 21, no. 3. DOI: 10.18564/jasss.3660.

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