Communications - Scientific Letters of the University of Zilina 2024, 26(3):B167-B174 | DOI: 10.26552/com.C.2024.031

Increasing the Traffic Safety Level of Rolling Stock by Wheel Condition Monitoring Using an Automated Measuring Complex

Sergii Kliuiev ORCID...1, Stanislav Semenov ORCID...1, Evgeny Mikhailov ORCID...1, Ján Dižo ORCID...2, *, Miroslav Blatnický ORCID...2, Vadym Ishchuk ORCID...2
1 Department of Logistics and Transport Safety, Volodymyr Dahl East Ukrainian National University, Kyiv, Ukraine
2 Department of Transport and Handling Machines, Faculty of Mechanical Engineering, University of Zilina, Zilina, Slovak Republic

The rail rolling stock undercarriage condition monitoring is proposed by using an automated measuring system, located on the railway track and measuring the specified parameters of the wheels directly, while the train is moving. Regular undercarriage condition monitoring reduces the costs of preventive maintenance of rolling stock without compromising the traffic safety. An algorithm has been developed for the operation of a special software package for visualizing and assessing monitoring data on the condition of the undercarriage of rail rolling stock. The software package consists of separate software modules that can be used independently of each other. It is possible to make short- or long-term predictions of the behavior of any of the monitored parameters using an proposed automated measuring system.

Keywords: rolling stock, carriage part, wheel, rail, measurements, defect, measurement accuracy, traffic safety
Grants and funding:

This research was supported by the project VEGA 1/0305/23: The research of dynamic properties of mechanical systems of railway vehicles with flexible structural components when running on a track and by the project KEGA No. 031ZU-4/2023: Development of key competencies of the graduate of the study program Vehicles and Engines.

Conflicts of interest:

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Received: February 12, 2024; Accepted: May 4, 2024; Prepublished online: May 23, 2024; Published: July 11, 2024  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Kliuiev, S., Semenov, S., Mikhailov, E., Dižo, J., Blatnický, M., & Ishchuk, V. (2024). Increasing the Traffic Safety Level of Rolling Stock by Wheel Condition Monitoring Using an Automated Measuring Complex. Communications - Scientific Letters of the University of Zilina, 26(3), B167-174. doi: 10.26552/com.C.2024.031
Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. ROSIC, S., STAMENKOVIC, D., BANIC, M., SIMONOVIC, M., RISTIC-DURRANT, D., ULIANOV, C. Analysis of the safety level of obstacle detection in autonomous railway vehicles. Acta Polytechnica Hungarica [online]. 2022, 19(3), p. 187-205. ISSN 1785-8860, eISSN 2064-2687. Available from: https://doi.org/10.12700/APH.19.3.2022.3.15 Go to original source...
    2. KAGRAMANIAN, A., AULIN, D., TRUBCHANINOVA, K., CABAN, J., VORONIN, A., BASOV, A. Perspectives of multifunctional integrated suburban-urban rail transport development. Scientific Journal of Silesian University of Technology. Series Transport [online]. 2023, 120, p. 105-115. ISSN 0209-3324, eISSN 2450-1549. Available from: https://doi.org/10.20858/sjsutst.2023.120.7 Go to original source...
    3. LOVSKA, A., FOMIN, O., PISTEK, V., KUCERA, P. Dynamic load and strength determination of carrying structure of wagons transported by ferries. Journal of Marine Science and Engineering [online]. 2020, 8(11), p. 1-14. eISSN 2077-1312. Available from: https://doi.org/10.3390/jmse8110902 Go to original source...
    4. FOMIN, O., LOVSKA, A., MASILYEV, V., TSYMBALIUK, A., BURLUTSKI, O. Determining strength indicators for the bearing structure of a covered wagon's body made from round pipes when transported by a railroad ferry. Eastern-European Journal of Enterprise Technologies [online]. 2019, 1(1-97), p. 33-40. ISSN 1729-3774, eISSN 1729-4061. Available from: https://doi.org/10.15587/1729-4061.2019.154282 Go to original source...
    5. LYOVIN, B. Integrated monitoring of transport infrastructure. Science and Technology of Railways. 2017, 1, p. 14-21, ISSN 2587-5752.
    6. MORAIS, P., MORAIS, J., SANTOS, C., PAIXAO, A., FORTUNATO, E., ASSEICEIRO, F., ALVARENGA, P., GOMES, L. Continuous monitoring and evaluation of railway tracks: proof of concept. Procedia Structural Integrity [online]. 2019, 17, p. 419-426. eISSN 2452-3216. Available from: https://doi.org/10.1016/j.prostr.2019.08.055 Go to original source...
    7. KLIUIEV, S., MEDVEDIEV, I., KHALIPOVA, N. Study of railway traffic safety based on the railway track condition monitoring system. IOP Conference Series: Materials Science and Engineering [online]. 2020, 985, 012012. ISSN 1757-899X. Available from: https://doi.org/10.1088/1757-899X/985/1/012012 Go to original source...
    8. KLIUIEV, S. O. Ensuring the safety of railway transport in conditions of digitalization (in Ukrainian). Bulletin of the SNU named after V. Dalya. 2020, 5(261), p. 14-18, ISSN 1998-7927.
    9. PAPAELIAS, M., AMINI, A., HUANG, Z., VALLELY, P., DIAS, D. C., KERKYRAS, S. Online condition monitoring of rolling stock wheels and axle bearings. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit [online], 2014, 230(3), p. 709-723. ISSN 0954-4097, eISSN 2041-3017. Available from: https://doi.org/10.1177/0954409714559758 Go to original source...
    10. HAUSER, V., NOZHENKO, O., KRAVCHENKO, K., LOULOVA, M., GERLICI, J., LACK, T. Impact of wheelset steering and wheel profile geometry to the vehicle behavior when passing curved track. Manufacturing Technology [online]. 2017, 17(3), p. 306-312. ISSN 1213-2489, eISSN 2787-9402. Available from: https://doi.org/10.21062/ujep/x.2017/a/1213-2489/MT/17/3/306 Go to original source...
    11. GERLICI, J., LACK, T., HARUSINEC, J. Development of test stand prototype for rail vehicles brake components testing. Communications - Scientific Letters of the University of Zilina [online]. 2014, 16(3a), p. 27-32. ISSN 1335-4205, eISSN 2585-7878. Available from: https://doi.org/10.26552/com.C.2014.3A.27-32 Go to original source...
    12. KARDAS-CINAL, E. Statistical analysis of dynamical quantities related to running safety and ride comfort of a railway vehicle. Scientific Journal of Silesian University of Technology. Series Transport [online]. 2020, 106, p. 63-72. ISSN 0209-3324, eISSN 2450-1549. Available from: https://doi.org/10.20858/sjsutst.2020.106.5 Go to original source...
    13. TURABIMANA, P., NKUNDINEZA, C. Development of an on-board measurement system for railway vehicle wheel flange wear. Sensors [online]. 2020, 20(1), 303. eISSN 1424-8220. Available from: https://doi.org/10.3390/s20010303 Go to original source...
    14. ASKEROV, H., VAKULENKO, I., GRISCHENKO, N. Insights into factors of damage of surface rolling of railway wheels during operation. Scientific Journal of Silesian University of Technology. Series Transport [online]. 2019, 105, p. 27-33. ISSN 0209-3324, eISSN 2450-1549. Available from: https://doi.org/10.20858/sjsutst.2019.105.3 Go to original source...
    15. ENTEZAMI, M., ROBERTS, C., WESTON, P., STEWART, E., AMINI, A., PAPAELIAS, M. Perspectives on railway axle bearing condition monitoring. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit [online]. 2020, 234(1), p. 17-31. ISSN 0954-4097, eISSN 2041-3017. Available from: https://doi.org/10.1177/0954409719831822 Go to original source...
    16. Transportation Research Board. Rail safety IDEAS programme annual report. Washington, DC: The National Academy of Science, 2018.
    17. DUTTA, S., HARRISON, T. J., SARMIENTO-CARNEVALI, M. L., WARD, C. P., DIXON, R. Modelling and controller design for self-adjusting railway track switch system. In: 7th Transport Research Arena TRA: proceedings [online]. 2018. Available from: https://hdl.handle.net/2134/32959
    18. GIANG, K. L. E. Enhancing traffic safety: a comprehensive approach through real-time data and intelligent transportation systems. Scientific Journal of Silesian University of Technology. Series Transport [online]. 2024, 122, p. 129-149. ISSN 0209-3324, eISSN 2450-1549.Available from: https://doi.org/10.20858/sjsutst.2024.122.8 Go to original source...
    19. MACIOSZEK, E. Analysis of the rail cargo transport volume in Poland in 2010-2021. Scientific Journal of Silesian University of Technology. Series Transport [online]. 2023, 119, p. 125-140. ISSN 0209-3324, eISSN 2450-1549. Available from: https://doi.org/10.20858/sjsutst.2023.119.7 Go to original source...
    20. LOVSKAYA, A. Assessment of dynamic efforts to bodies of wagons at transportation with railway ferries. Eastern-European Journal of Enterprise Technologies [online]. 2014, 3(4), p. 36-41. ISSN 1729-3774, eISSN 1729-4061. Available from: https://doi.org/10.15587/1729-4061.2014.24997 Go to original source...
    21. AMINI, A., ENTEZAMI, M., PAPAELIAS, M. Onboard detection of railway axle bearing defects using envelope analysis of high frequency acoustic emission signals. Case Studies in Nondestructive Testing and Evaluation [online]. 2016, 6(Part A), p. 8-16. ISSN 2214-6571. Available from: https://doi.org/10.1016/j.csndt.2016.06.002 Go to original source...
    22. LUBNA, M., MEHDI, G., ZIED, B. Smart gas sensors: materials, technologies, practical applications, and use of machine learning - a review. Journal of Applied and Computational Mechanics [online]. 2023, 9(3), p. 775-803. eISSN 2383-4536. Available from: https://doi.org/10.22055/JACM.2023.41985.3851 Go to original source...
    23. KUMAR, S., GOYAL, D., DHAMI, S. S. Statistical and frequency analysis of acoustic signals for condition monitoring of ball bearing. Materials Today: Proceedings [online]. 2018, 5(2), p. 5186-5194. eISSN 2214-7853. Available from: https://doi.org/10.1016/j.matpr.2017.12.100 Go to original source...
    24. YANG, T., DU, C., ZHOU, S. Study on reverberation suppression method combined with prewhitening and wavelet transform. Acoustic Technique [online]. 2021, 40, p. 110-116, ISSN 1819-2408. Go to original source...
    25. SUN, R.-B., YANG, Z.-B., ZHAI, Z., CHEN, X.-F. Sparse representation based on parametric impulsive dictionary design for bearing fault diagnosis. Mechanical Systems and Signal Processing [online]. 2019, 122, p. 737-753. eISSN 1096-1216. Available from: https://doi.org/10.1016/j.ymssp.2018.12.054 Go to original source...
    26. CHEN, Y., NING, P., FAN, T. An improved fast spectral kurtosis algorithm in bearing fault diagnosis for a motor drive system. In: IEEE 6th International Electrical and Energy Conference CIEEC: proceedings [online]. IEEE. 2023. eISBN 979-8-3503-4667-1. Available from: https://doi.org/10.1109/CIEEC58067.2023.10166214 Go to original source...
    27. FISCHER, S., SZURKE, S. K. Detection process on energy loss in electric railway vehicles. Facta Universitatis, Series: Mechanical Engineering [online]. 2023, 21(1), p. 81-99. ISSN 0354-2025, eISSN 2335-0164. Available from: https://doi.org/10.22190/FUME221104046F Go to original source...
    28. SEMENOV, S., MIKHAILOV, E., DIZO, J., BLATNICKY, M. The research of running resistance of a railway wagon with various wheel designs. In: Transportation Science and Technology Lecture Notes in Intelligent Transportation and Infrastructure TRANSBALTICA XII: proceedings [online]. 2022. ISBN 978-3-030-94776-7, eISSN 2523-3459, p. 110-119. Available from: https://doi.org/10.1007/978-3-030-94774-3_11 Go to original source...
    29. SEMENOV, S., MIKHAILOV, E., KLIUIEV, S., DIZO, J., BLATNICKY, M., ISHCHUK, V. Improving the energy efficiency of a tram's running gear. Acta Polytechnica [online]. 2023, 63(3), p. 216-226. ISSN 1210-2709, eISSN 1805-2363. Available from: https://doi.org/10.14311/AP.2023.63.0216 Go to original source...
    30. VATULIA, G., LOVSKA, A., PAVLIUCHENKOV, M., NERUBATSKYI, V., OKOROKOV, A., HORDIIENKO, D., VERNIGORA, R., ZHURAVEL, I. Determining patterns of vertical load on the prototype of a removable module for long-size cargoes. Eastern-European Journal of Enterprise Technologies [online]. 2022, 6(7), p. 21-29. ISSN 1729-3774, eISSN 1729-4061. Available from: https://doi.org/10.15587/1729-4061.2022.266855 Go to original source...
    31. DAI, W., MO, Z., LUO, CH., JIANG, J., MIAO, Q. Bearing fault diagnosis based on reinforcement learning and kurtosis. In: 2019 Prognostics and System Health Management Conference PHM-Qingdao: proceedings [online]. IEEE. 2019. eISBN 978-1-7281-0861-2. Available from: https://doi.org/10.1109/PHM-Qingdao46334.2019.8942977 Go to original source...
    32. OSORIO SANTANDER, E. J., NETO, S., VAZ, L.V., MONTEIRO, U. A. Using spectral kurtosis for selection of the frequency bandwidth containing the fault signature in rolling bearings. Marine Systems and Ocean Technology [online]. 2020, 15, p. 243-252. ISSN 1679-396X, eISSN 2199-4749. Available from: https://doi.org/10.1007/s40868-020-00084-2 Go to original source...

    This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.


    Return to the content