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Process Monitoring in Heavy Duty Drilling Rigs—Data Acquisition System and Cycle Identification Algorithms

Author

Listed:
  • Jacek Wodecki

    (Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15, 50-421 Wrocław, Poland)

  • Mateusz Góralczyk

    (Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15, 50-421 Wrocław, Poland)

  • Pavlo Krot

    (Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15, 50-421 Wrocław, Poland)

  • Bartłomiej Ziętek

    (Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15, 50-421 Wrocław, Poland)

  • Jaroslaw Szrek

    (Faculty of Mechanical Engineering, Wroclaw University of Science and Technology, Łukasiewicza 5/7, 50-370 Wrocław, Poland)

  • Magdalena Worsa-Kozak

    (Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15, 50-421 Wrocław, Poland)

  • Radoslaw Zimroz

    (Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15, 50-421 Wrocław, Poland)

  • Paweł Śliwiński

    (KGHM Polska Miedź S.A., M. Skłodowskiej-Curie 48, 59-301 Lubin, Poland)

  • Andrzej Czajkowski

    (Mine Master Spółka z o.o., Wilków, ul. Dworcowa 27, 59-500 Złotoryja, Poland)

Abstract

The monitoring of drilling processes is a well-known topic in the mining industry. It is widely used for rock mass characterization, bit wear monitoring and drilling process assessment. However on-board monitoring systems used for this purpose are installed only on a limited number of machines, and breakdowns are possible. There is a need for a data acquisition system that can be used on different drilling rigs and for an automatic data analysis procedure. In this paper, we focused on the automatic detection of drilling cycles, presenting a simple yet reliable system to be universally installed on drilling rigs. The proposed solution covers hardware and software. It is based on the measurement of electric current and acoustic signals. The signal processing methods include threshold-based segmentation, a short-time envelope spectrum and a spectrum for the representation of results. The results of the research have been verified on a real drilling rig within the testing site of its manufacturer by comparing the results with the data of the on-board monitoring system installed on the machine. Novel aspects of our approach include the detection of the pre-boring stage, which has an intermediate amplitude that masks the real drilling cycles, and the use of the percussion instantaneous frequency, which is estimated by acoustic recordings.

Suggested Citation

  • Jacek Wodecki & Mateusz Góralczyk & Pavlo Krot & Bartłomiej Ziętek & Jaroslaw Szrek & Magdalena Worsa-Kozak & Radoslaw Zimroz & Paweł Śliwiński & Andrzej Czajkowski, 2020. "Process Monitoring in Heavy Duty Drilling Rigs—Data Acquisition System and Cycle Identification Algorithms," Energies, MDPI, vol. 13(24), pages 1-21, December.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:24:p:6748-:d:465842
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    References listed on IDEAS

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    1. Pengqi Qiu & Xuehui Li & Jianguo Ning & Jun Wang & Shang Yang, 2019. "Study on Thermal Energy Conversion Theory in Drilling Process of Coal and Rock Mass with Different Stresses," Energies, MDPI, vol. 12(22), pages 1-14, November.
    2. Aditya Sharma & Saket Srivastava & Catalin Teodoriu, 2020. "Experimental Design, Instrumentation, and Testing of a Laboratory-Scale Test Rig for Torsional Vibrations—The Next Generation," Energies, MDPI, vol. 13(18), pages 1-19, September.
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    Cited by:

    1. Dawid Szurgacz, 2021. "Dynamic Analysis for the Hydraulic Leg Power of a Powered Roof Support," Energies, MDPI, vol. 14(18), pages 1-12, September.
    2. Dawid Szurgacz & Sergey Zhironkin & Jiří Pokorný & A. J. S. (Sam) Spearing & Stefan Vöth & Michal Cehlár & Izabela Kowalewska, 2021. "Development of an Active Training Method for Belt Conveyor," IJERPH, MDPI, vol. 19(1), pages 1-12, December.
    3. Sergey Zhironkin & Dawid Szurgacz, 2022. "Mining Technologies Innovative Development: Industrial, Environmental and Economic Perspectives," Energies, MDPI, vol. 15(5), pages 1-5, February.

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