Devising a procedure to form the diagnostic parameters for locomotives using a principal components analysis

Authors

DOI:

https://doi.org/10.15587/1729-4061.2021.230293

Keywords:

principal components analysis, parameter informativeness, latent diagnostic parameter, hydraulic transmission

Abstract

Modern diagnostic systems are characterized by that the flow of diagnostic information requires significant computational resources to process. In order to improve the reliability of the object to be diagnosed and reduce operating costs, it is necessary to improve procedures for analyzing diagnostic results. This paper suggests a procedure to form the diagnostic features of locomotive nodes based on the use of a principal components analysis. The proposed approach is distinguished by a decrease in the dimensionality of the input set of diagnostic features in order to select the sets of interconnected diagnostic parameters. Based on the selection of the sets of interconnected diagnostic features, constructing new latent diagnostic parameters has been proposed. A latent diagnostic parameter contains information that combines data from several initial diagnostic features. The result of the method is a set of latent diagnostic parameters that do not correlate with each other and reflect the behavior of the object to be diagnosed from different technical points. The application of a sufficient number of latent diagnostic parameters involved the scree test method. This paper reports the results from using the proposed approach for treating the results from diagnosing the hydraulic transmissions in locomotives. The result from applying the procedure has made it possible to propose using three latent diagnostic parameters to assess the technical condition of a locomotive’s hydraulic transmission during bench tests. The suggested parameters contain 90 % of the original information and reflect losses in the transmission, as well as the load at the input and output of the transmission.

Author Biographies

Borys Bodnar, Dnipro National University of Railway Transport named after Academician V. Lazaryan

Doctor of Technical Sciences, Professor, First Vice-Rector

Department of Locomotives

Oleksandr Ochkasov, Dnipro National University of Railway Transport named after Academician V. Lazaryan

PhD, Associate Professor

Department of Locomotives

References

  1. Tkachenko, V., Sapronova, S., Kulbovskiy, I., Fomin, O. (2017). Research into resistance to the motion of railroad undercarriages related to directing the wheelsets by a rail track. Eastern-European Journal of Enterprise Technologies, 5 (7 (89)), 65–72. doi: https://doi.org/10.15587/1729-4061.2017.109791
  2. Sapronova, S., Tkachenko, V., Fomin, O., Hatchenko, V., Maliuk, S. (2017). Research on the safety factor against derailment of railway vehicless. Eastern-European Journal of Enterprise Technologies, 6 (7 (90)), 19–25. doi: https://doi.org/10.15587/1729-4061.2017.116194
  3. Kapitsa, M. I., Laguta, V. V. (2013). Modeli rezhimov diagnostirovaniya tyagovogo podvizhnogo sostava s zamenoy komplektuyuschih izdeliy. Elektromahnitna sumisnist ta bezpeka na zaliznychnomu transport, 5, 56–62.
  4. Bodnar', B. E., Ochkasov, A. B. (2001). Vybor diagnosticheskih parametrov s ispol'zovaniem informatsionno-vesovogo kriteriya. Sbornik trudov DIIT: Transport, 7, 35–37.
  5. Pashkovskiy, G. S. (1981). Zadachi optimal'nogo obnaruzheniya i poiska otkazov v REA. Moscow: Radio i svyaz', 280.
  6. Pushkarev, I. F., Strekopytov, V. V. (1988). Nadezhnost' i tehnicheskaya diagnostika lokomotivov. Leningrad, 61.
  7. Lin, L., Jiang, X., Huang, Z., Hu, H. (2010). Application of advanced fault diagnosis technology in electric locomotives. International Journal of Modelling, Identification and Control, 10 (3/4), 292. doi: https://doi.org/10.1504/ijmic.2010.034581
  8. Falendysh, A., Sumtsov, A., Artemenko, O., Klecka, O. (2016). Simulation of changes in the steady state availability factor of shunting locomotives for various maintenance systems. Eastern-European Journal of Enterprise Technologies, 1 (3 (79)), 24–31. doi: https://doi.org/10.15587/1729-4061.2016.60640
  9. Kapitsa, M., Laguta, V., Kozik, Y. (2018). Selecting the Parameters of The Diagnosis of Frame Insulation Condition in Electrical Machines of Locomotives. International Journal of Engineering & Technology, 7 (4.3), 110. doi: https://doi.org/10.14419/ijet.v7i4.3.19718
  10. Bannikov, D., Yakovlev, S. (2020). Development of dynamic integral evaluation method of technical state of one-section electric locomotive body. Eastern-European Journal of Enterprise Technologies, 1 (7 (103)), 57–64. doi: https://doi.org/10.15587/1729-4061.2020.192468
  11. Moiseenko, V., Kameniev, O., Gaievskyi, V. (2017). Predicting a technical condition of railway automation hardware under conditions of limited statistical data. Eastern-European Journal of Enterprise Technologies, 3 (9 (87)), 26–35. doi: https://doi.org/10.15587/1729-4061.2017.102005
  12. Orlov, A. I., Lutsenko, E. V. (2016). Methods of reducing space dimension of statistical data. Nauchniy zhurnal KubGAU, 119, 92–107. Available at: https://elibrary.ru/item.asp?id=26148522
  13. Ayvazyan, S. A., Buhshtaber, V. M., Enyukov, I. S., Meshalkin, L. D.; Ayvazyan, S. A. (Ed.) (1989). Prikladnaya statistika: Klassifikatsii i snizhenie razmernosti. Moscow: Finansy i statistika, 607.
  14. Subbotin, S. A. (2013). Sample formation and reduction for data mining. Radio Electronics, Computer Science, Control, 1, 113–118. doi: https://doi.org/10.15588/1607-3274-2013-1-18
  15. Bosov, A., Loza, P. (2014). Creation of an index of arbitrary process. Zbirnyk naukovykh prats Donetskoho instytutu zaliznychnoho transportu, 38, 68–73. Available at: http://nbuv.gov.ua/UJRN/znpdizt_2014_38_13
  16. Yin, S., Ding, S. X., Xie, X., Luo, H. (2014). A Review on Basic Data-Driven Approaches for Industrial Process Monitoring. IEEE Transactions on Industrial Electronics, 61 (11), 6418–6428. doi: https://doi.org/10.1109/tie.2014.2301773
  17. Jolliffe, I. T., Cadima, J. (2016). Principal component analysis: a review and recent developments. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374 (2065), 20150202. doi: https://doi.org/10.1098/rsta.2015.0202
  18. Bodnar, B., Bolzhelarskyi, Y., Ochkasov, O., Hryshechkina, T., Černiauskaite, L. (2018). Determination of integrated indicator for analysis of the traffic safety condition for traction rolling stock. Paper presented at the 12th International Conference on Intelligent Technologies in Logistics and Mechatronics Systems, ITELMS 2018. Panevėžys, 45–54.
  19. Bodnar, B., Ochkasov, O., Bodnar, E., Hryshechkina, T., Keršys, R. (2018). Safety performance analysis of the movement and operation of locomotives. Proceedings of 22nd International Scientific Conference, 839–843.
  20. Nadir, F., Elias, H., Messaoud, B. (2020). Diagnosis of defects by principal component analysis of a gas turbine. SN Applied Sciences, 2 (5). doi: https://doi.org/10.1007/s42452-020-2796-y
  21. Mnassri, B., Adel, E. M. E., Ananou, B., Ouladsine, M. (2009). Fault Detection and Diagnosis Based on PCA and a New Contribution Plot. IFAC Proceedings Volumes, 42 (8), 834–839. doi: https://doi.org/10.3182/20090630-4-es-2003.00137
  22. Doorsamy, W., Cronje, W. A. (2015). A method for fault detection on synchronous generators using modified principal component analysis. 2015 IEEE International Conference on Industrial Technology (ICIT). doi: https://doi.org/10.1109/icit.2015.7125162
  23. Zheng, M., Wu, L., Li, L., Liu, C., Wang, L., Sun, S. (2017). A modified method for fault detection and isolation of redundant inerial measurement unit in dynamic environment. 2017 36th Chinese Control Conference (CCC). doi: https://doi.org/10.23919/chicc.2017.8028460
  24. Cattell, R. B. (1966). The Scree Test For The Number Of Factors. Multivariate Behavioral Research, 1 (2), 245–276. doi: https://doi.org/10.1207/s15327906mbr0102_10
  25. Zhukovytskyy, I. V., Kliushnyk, I. A., Ochkasov, O. B., Korenyuk, R. O. (2015). Information-measuring test system of diesel locomotive hydraulic transmissions. Science and Transport Progress. Bulletin of Dnipropetrovsk National University of Railway Transport, 5 (59), 53–65. doi: https://doi.org/10.15802/stp2015/53159
  26. Bodnar, B., Ochkasov, O., Bobyr, D., Korenyuk, R., Bazaras, Z. (2018). Using the Self-Braking Method when the Post-Overhaul Diagnostics of Diesel-Hydraulic Locomotives. In: 2018 Transport means proceedings of the international conference. Kaunas, 914–919.
  27. hukovyts’kyy, I., Kliushnyk, I. (2018). Development of a self­diagnostics subsystem of the information­measuring system using anfis controllers. Eastern-European Journal of Enterprise Technologies, 1 (9 (91)), 11–19. doi: https://doi.org/10.15587/1729-4061.2018.123591

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Published

2021-04-20

How to Cite

Bodnar, B., & Ochkasov, O. (2021). Devising a procedure to form the diagnostic parameters for locomotives using a principal components analysis. Eastern-European Journal of Enterprise Technologies, 2(1 (110), 97–103. https://doi.org/10.15587/1729-4061.2021.230293

Issue

Vol. 2 No. 1 (110) (2021): Engineering technological systems

Section

Engineering technological systems

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Copyright (c) 2021 Borys Bodnar, Oleksandr Ochkasov

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