IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i5p2785-d759979.html
   My bibliography  Save this article

A Preliminary Studies of the Impact of a Conveyor Belt on the Noise Emission

Author

Listed:
  • Piotr Bortnowski

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

  • Robert Król

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

  • Anna Nowak-Szpak

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

  • Maksymilian Ozdoba

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

Abstract

This article performs a comparative analysis of noise generated by conveyor belts with different design parameters. The study was conducted for belts with the same tensile strength, differing in the physical parameters of the cover rubber. Noise emission measurements were performed on a laboratory belt conveyor. The test on the stand allowed for the determination of the noise emission as a function of variable operating parameters: the tensioning force and linear speed of the belt. Research results indicated a significant impact of speed on the emitted noise. The effect of belt tension on noise emission is small, and it is definitely less significant than the effect of linear speed. The results also show that it is possible to select a conveyor belt that emits less noise under the same operating conditions. The analysis of the results allowed us to determine the impact of the physical parameters of the belt covers on the emitted noise.

Suggested Citation

  • Piotr Bortnowski & Robert Król & Anna Nowak-Szpak & Maksymilian Ozdoba, 2022. "A Preliminary Studies of the Impact of a Conveyor Belt on the Noise Emission," Sustainability, MDPI, vol. 14(5), pages 1-15, February.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:2785-:d:759979
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/5/2785/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/5/2785/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Middelberg, Arno & Zhang, Jiangfeng & Xia, Xiaohua, 2009. "An optimal control model for load shifting - With application in the energy management of a colliery," Applied Energy, Elsevier, vol. 86(7-8), pages 1266-1273, July.
    2. 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.
    3. Piotr Bortnowski & Anna Nowak-Szpak & Robert Król & Maksymilian Ozdoba, 2021. "Analysis and Distribution of Conveyor Belt Noise Sources under Laboratory Conditions," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Claudia Violeta Pop & Daniel Fodorean & Dan-Cristian Popa, 2022. "Structural Analysis of an In-Wheel Motor with Integrated Magnetic Gear Designed for Automotive Applications," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
    2. Karol Semrád & Katarína Draganová, 2022. "Non-Destructive Testing of Pipe Conveyor Belts Using Glass-Coated Magnetic Microwires," Sustainability, MDPI, vol. 14(14), pages 1-15, July.
    3. Dawid Szurgacz & Beata Borska & Sergey Zhironkin & Ryszard Diederichs & Anthony J. S. Spearing, 2022. "Optimization of the Load Capacity System of Powered Roof Support: A Review," Energies, MDPI, vol. 15(16), pages 1-15, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. S.R. Patterson & E. Kozan & P. Hyland, 2016. "An integrated model of an open-pit coal mine: improving energy efficiency decisions," International Journal of Production Research, Taylor & Francis Journals, vol. 54(14), pages 4213-4227, July.
    2. Jin, Hongyang & Li, Zhengshuo & Sun, Hongbin & Guo, Qinglai & Chen, Runze & Wang, Bin, 2017. "A robust aggregate model and the two-stage solution method to incorporate energy intensive enterprises in power system unit commitment," Applied Energy, Elsevier, vol. 206(C), pages 1364-1378.
    3. Dashti, Reza & Afsharnia, Saeed & Ghasemi, Hassan, 2010. "A new long term load management model for asset governance of electrical distribution systems," Applied Energy, Elsevier, vol. 87(12), pages 3661-3667, December.
    4. Rastegar, Mohammad & Fotuhi-Firuzabad, Mahmud & Aminifar, Farrokh, 2012. "Load commitment in a smart home," Applied Energy, Elsevier, vol. 96(C), pages 45-54.
    5. Rajeev, T. & Ashok, S., 2015. "Dynamic load-shifting program based on a cloud computing framework to support the integration of renewable energy sources," Applied Energy, Elsevier, vol. 146(C), pages 141-149.
    6. Muller, C.J. & Craig, I.K., 2016. "Energy reduction for a dual circuit cooling water system using advanced regulatory control," Applied Energy, Elsevier, vol. 171(C), pages 287-295.
    7. Obara, Shin'ya & Hamanaka, Ryo & El-Sayed, Abeer Galal, 2019. "Design methods for microgrids to address seasonal energy availability – A case study of proposed Showa Antarctic Station retrofits," Applied Energy, Elsevier, vol. 236(C), pages 711-727.
    8. Märkle-Huß, Joscha & Feuerriegel, Stefan & Neumann, Dirk, 2018. "Large-scale demand response and its implications for spot prices, load and policies: Insights from the German-Austrian electricity market," Applied Energy, Elsevier, vol. 210(C), pages 1290-1298.
    9. Boßmann, Tobias & Eser, Eike Johannes, 2016. "Model-based assessment of demand-response measures—A comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1637-1656.
    10. Kirchem, Dana & Lynch, Muireann Á. & Bertsch, Valentin & Casey, Eoin, 2020. "Modelling demand response with process models and energy systems models: Potential applications for wastewater treatment within the energy-water nexus," Applied Energy, Elsevier, vol. 260(C).
    11. Xia, Xiaohua & Zhang, Jiangfeng, 2013. "Mathematical description for the measurement and verification of energy efficiency improvement," Applied Energy, Elsevier, vol. 111(C), pages 247-256.
    12. Chen, Runze & Sun, Hongbin & Guo, Qinglai & Jin, Hongyang & Wu, Wenchuan & Zhang, Boming, 2015. "Profit-seeking energy-intensive enterprises participating in power system scheduling: Model and mechanism," Applied Energy, Elsevier, vol. 158(C), pages 263-274.
    13. Nataf, Kalen & Bradley, Thomas H., 2016. "An economic comparison of battery energy storage to conventional energy efficiency technologies in Colorado manufacturing facilities," Applied Energy, Elsevier, vol. 164(C), pages 133-139.
    14. Xiaoqing Hu & Beibei Wang & Shengchun Yang & Taylor Short & Lei Zhou, 2015. "A Closed-Loop Control Strategy for Air Conditioning Loads to Participate in Demand Response," Energies, MDPI, vol. 8(8), pages 1-32, August.
    15. Paweł Bogacz & Łukasz Cieślik & Dawid Osowski & Paweł Kochaj, 2022. "Analysis of the Scope for Reducing the Level of Energy Consumption of Crew Transport in an Underground Mining Plant Using a Conveyor Belt System Mining Plant," Energies, MDPI, vol. 15(20), pages 1-16, October.
    16. Numbi, B.P. & Xia, X., 2015. "Systems optimization model for energy management of a parallel HPGR crushing process," Applied Energy, Elsevier, vol. 149(C), pages 133-147.
    17. van Staden, Adam Jacobus & Zhang, Jiangfeng & Xia, Xiaohua, 2011. "A model predictive control strategy for load shifting in a water pumping scheme with maximum demand charges," Applied Energy, Elsevier, vol. 88(12), pages 4785-4794.
    18. Stötzer, Martin & Hauer, Ines & Richter, Marc & Styczynski, Zbigniew A., 2015. "Potential of demand side integration to maximize use of renewable energy sources in Germany," Applied Energy, Elsevier, vol. 146(C), pages 344-352.
    19. 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.
    20. Moreno, Blanca & García-Álvarez, María Teresa & Ramos, Carmen & Fernández-Vázquez, Esteban, 2014. "A General Maximum Entropy Econometric approach to model industrial electricity prices in Spain: A challenge for the competitiveness," Applied Energy, Elsevier, vol. 135(C), pages 815-824.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:2785-:d:759979. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.