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Detection of Blockages of the Belt Conveyor Transfer Point Using an RGB Camera and CNN Autoencoder

Author

Listed:
  • Piotr Bortnowski

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

  • Horst Gondek

    (VSB—Department of Machine and Industrial Design, Technical University of Ostrava, 17 Listopadu 2172/15, 708 00 Ostrava, Czech Republic)

  • Robert Król

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

  • Daniela Marasova

    (Institute of Logistics and Transport, Faculty BERG, Technical University of Košice, Park Komenského 14, 043 84 Košice, Slovakia)

  • Maksymilian Ozdoba

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

Abstract

In the material transfer area, the belt is exposed to considerable damage, the energy of falling material is lost, and there is significant dust and noise. One of the most common causes of failure is transfer chute blockage, when the flow of material in the free fall or loading zone is disturbed by oversized rock parts or other objects, e.g., rock bolts. The failure of a single transfer point may cause the entire transport route to be excluded from work and associated with costly breakdowns. For this reason, those places require continuous monitoring and special surveillance measures. The number of methods for monitoring this type of blockage is limited. The article presents the research results on the possibility of visual monitoring of the transfer operating status on an object in an underground copper ore mine. A standard industrial RGB camera was used to obtain the video material from the transfer point area, and the recorded frames were processed by a detection algorithm based on a neural network. The CNN autoencoder was taught to reconstruct the image of regular transfer operating conditions. A data set with the recorded transfer blockage state was used for validation.

Suggested Citation

  • Piotr Bortnowski & Horst Gondek & Robert Król & Daniela Marasova & Maksymilian Ozdoba, 2023. "Detection of Blockages of the Belt Conveyor Transfer Point Using an RGB Camera and CNN Autoencoder," Energies, MDPI, vol. 16(4), pages 1-18, February.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1666-:d:1060808
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    References listed on IDEAS

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    1. Jiang Yao & Zhiqiang Wang & Chunhui Liu & Guichen Huang & Qingbo Yuan & Kai Xu & Wenhui Zhang, 2022. "Detection Method of Crushing Mouth Loose Material Blockage Based on SSD Algorithm," Sustainability, MDPI, vol. 14(21), pages 1-16, November.
    2. Błażej Doroszuk & Robert Król & Jarosław Wajs, 2021. "Simple Design Solution for Harsh Operating Conditions: Redesign of Conveyor Transfer Station with Reverse Engineering and DEM Simulations," Energies, MDPI, vol. 14(13), pages 1-13, July.
    3. Mirosław Bajda & Monika Hardygóra, 2021. "Analysis of the Influence of the Type of Belt on the Energy Consumption of Transport Processes in a Belt Conveyor," Energies, MDPI, vol. 14(19), pages 1-17, September.
    4. Dawid Szurgacz & Sergey Zhironkin & Stefan Vöth & Jiří Pokorný & A.J.S. (Sam) Spearing & Michal Cehlár & Marta Stempniak & Leszek Sobik, 2021. "Thermal Imaging Study to Determine the Operational Condition of a Conveyor Belt Drive System Structure," Energies, MDPI, vol. 14(11), pages 1-18, June.
    5. Mirosław Bajda & Monika Hardygóra & Daniela Marasová, 2022. "Energy Efficiency of Conveyor Belts in Raw Materials Industry," Energies, MDPI, vol. 15(9), pages 1-6, April.
    6. Piotr Bortnowski & Adam Gładysiewicz & Lech Gładysiewicz & Robert Król & Maksymilian Ozdoba, 2022. "Conveyor Intermediate TT Drive with Power Transmission at the Return Belt," Energies, MDPI, vol. 15(16), pages 1-17, August.
    7. Przemyslaw Dabek & Jaroslaw Szrek & Radoslaw Zimroz & Jacek Wodecki, 2022. "An Automatic Procedure for Overheated Idler Detection in Belt Conveyors Using Fusion of Infrared and RGB Images Acquired during UGV Robot Inspection," Energies, MDPI, vol. 15(2), pages 1-20, January.
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