Forecasting the resource of machine parts based on the dynamics of changes in the wear mechanism using the neural network method
DOI:
https://doi.org/10.31891/2079-1372-2026-120-2-102-110Keywords:
parts life, wear, tribocoupling, change in wear mechanism, entropy transition detector, artificial neural network, condition-based maintenanceAbstract
The problem of predicting the residual resource of tribocouplings of resource-determining parts of automotive and agricultural machinery under conditions of operational change of the dominant wear mechanism is considered. It is shown that in real operating conditions the wear mechanism does not remain static: degradation of lubricants, change of load-speed regimes and variability of soil conditions cause a transition from a regular mechanism to an emergency one, which is accompanied by a sharp reduction in the residual resource of machine parts. A two-stage system for identifying the change in the dominant wear mechanism is proposed, combining a classifier based on long short-term memory with an entropy transition detector, which develops an entropy approach to the analysis of tribosystems. The data set is formed on the basis of a modified Archard model with five calibrated coefficients for different lubrication modes and a Palmgren-Miner model in the form of an endurance curve with realistic values of the basic number of cycles 108 ...109 for different materials of tribocoupling parts. Validation on eight scenarios of transition between wear mechanisms demonstrated reliable detection of the change in the dominant mechanism, the warning time for reaching a critical state of 229…593 hours for automotive parts and 13…21 hours for agricultural parts, which is 5.6…7.1% of the total resource and is sufficient for planning maintenance of machines
References
Kindrachuk, M.V., Labunets, V.F., Pashechko, M.I., & Korbut, Ye.V. (2009). Trybolohiia [Tribology]. NAU-druk. [in Ukrainian].
Dykha, O.V., & Velboi, V.P. (2014). Inzhenerni metody v trybotekhnisi [Engineering methods in tribotechnology]. KhNU. [in Ukrainian].
Aulin, V.V., et al. (2022). Parametry protsesu zmashchuvannia pry ekspluatatsiinomu znoshuvanni pidshypnykiv kolinchastoho vala avtomobilnykh dvyhuniv [Parameters of the lubrication process during operational wear of the crankshaft bearings of automobile engines]. Problemy trybolohii, 27(4/106), 69–81. https://doi.org/10.31891/2079-1372-2022-106-4-69-81 [in Ukrainian].
Aulin, V.V. (2013). Stan samoorhanizatsii seredovyshcha gruntu ta zakonomirnosti znosu robochykh orhaniv gruntoobrobnykh mashyn [Self-organization state of soil environment and wear patterns of tillage machine working parts]. Problemy trybolohii, (1), 114–119. https://tribology.khmnu.edu.ua/index.php/ProbTrib/article/view/157 [in Ukrainian].
Tykhyi, A.A., et al. (2024). Trybotekhnichni protsesy vzaiemodii gruntového seredovyshcha z robochymy orhanamy gruntoobrobnykh ta zemlereinykh mashyn, zmitsnenykh kompozytsiinymy materialamy [Tribotechnical processes of the soil environment interaction with the working bodies of soil tillage and earthmoving machines reinforced with composite materials]. Problemy trybolohii, 29(3/113), 79–88. https://doi.org/10.31891/2079-1372-2024-113-3-79-88 [in Ukrainian].
Stechyshyn, M.S., et al. (2024). Vplyv tekhnolohichnykh parametriv karboazotuvanny na znosostijkist stali 45 [Influence of carbonitriding technological parameters on wear resistance of steel 45]. Problems of Friction and Wear, 102(1), 45–53. https://doi.org/10.18372/0370-2197.3(84).13856 [in Ukrainian].
Aulin, V.V., et al. (2023). Vyiavlennia zmin kharakterystyk i vlastyvostei zon tertia detalei trybospriazhen system i ahrehativ mashyn na osnovi entropinoho pidkhodu [Detection of changes in the characteristics and properties of friction zones of parts of tribocoupling systems and machine assemblies based on the entropy approach]. Problemy trybolohii, 28(3/109), 58–63. https://doi.org/10.31891/2079-1372-2023-109-3-58-63 [in Ukrainian].
Bershchadskyi, L.I. (1990). Strukturna termodynamika trybosystem [Structural thermodynamics of tribosystems]. Znannia. [in Ukrainian].
Dvoruk, V.I., Mikosianchyk, O.O., & Mnatsakanov, R.H. (2015). Trybotekhnika [Tribotechnology]. NAU. [in Ukrainian].
Voitov, V.A., & Zakharchenko, M.B. (2015). Enerhetychna interpretatsiia protsesu znoshuvannіa trybosystem [Energy interpretation of the wear process of tribosystems]. Problemy trybolohii, (2), 75–82. https://tribology.khmnu.edu.ua/index.php/ProbTrib/issue/archive [in Ukrainian].
Dmytrychenko, M.F., Biliakových, O.M., & Savchuk, A.M. (2017). Trybolohiia [Tribology]. NTU. [in Ukrainian].
Dykha, O.V., & Hedzyuk, T.V. (2019). Kontaktna znosostijkist trybospriazhen pry hranychnomu zmashchuvanni [Contact wear resistance of tribocouplings under boundary lubrication]. Problemy trybolohii, 24(2/92), 28–35. https://doi.org/10.31891/2079-1372-2019-92-2-28-35 [in Ukrainian].
Chernets, M.V., & Andреikiv, O.Ye. (2017). Prohnozuvannia znosu i dovhovichnosti tsylindrychnykh opor kovzannia [Prediction of wear and durability of cylindrical sliding bearings]. NAN Ukrainy, FMI. [in Ukrainian].
Shevelia, V.V., & Oleksandrenko, V.P. (2009). Trybolohiia: fizychni osnovy, mekhanika i tekhnichni zastosuvannia [Tribology: physical foundations, mechanics and technical applications]. KhNU. [in Ukrainian].
Chumak, V.M., et al. (2025). Pidvyshchennia znosostijkosti ta nadiinosti resursovyznachalnykh detalei transportnoi ta silskohospodarskoi tekhniky metodamy inzhenernoi optymizatsii [Improving wear resistance and reliability of resource-determining parts of transport and agricultural machinery by engineering optimization methods]. Tsentralnoukrainskyi naukovyi visnyk. Tekhnichni nauky, 11(42, pt. 2), 143–159. https://doi.org/10.32515/2664-262X.2025.12(43).1.272-288 [in Ukrainian].
Chumak, V.M., et al. (2025). Universalnyi metod formalizatsii parametriv resursovyznachalnykh detalei transportnoi ta silskohospodarskoi tekhniky dlia system predyktyvnoho obsluhovuvannia [Universal method of formalizing parameters of resource-determining parts of transport and agricultural machinery for predictive maintenance systems]. Tsentralnoukrainskyi naukovyi visnyk. Tekhnichni nauky, (12(43), pt. 2), 204–219. https://doi.org/10.32515/2664-262X.2025.12(43).2.204-219 [in Ukrainian].
Lim, S.C., & Ashby, M.F. (1987). Wear-mechanism maps. Acta Metallurgica, 35(1), 1–24. https://doi.org/10.1016/0001-6160(87)90209-4
Hochreiter, S., & Schmidhuber, J. (1997). Long Short-Term Memory. Neural Computation, 9(8), 1735–1780. https://doi.org/10.1162/neco.1997.9.8.1735
Shah, R., et al. (2025). Machine Learning in Wear Prediction. Journal of Tribology, 147(4), 040801. https://doi.org/10.1115/1.4066865
Aulin, V.V., et al. (2021). Teoretychne obgruntuvannia vplyvu zminy dylatonykh i kompresijnykh zviаzkiv atomiv materialiv detalei mashyn na yikh trybologichnyi efekt [Theoretical justification of the influence of change of dilaton and compression bonds of atoms of materials of machine parts on their tribological effect]. Problemy trybolohii, 26(2/100), 71–78. https://doi.org/10.31891/2079-1372-2021-100-2-71-78 [in Ukrainian].
Chumak, V.M., et al. (2025). Modeliuvannia ta optymizatsiia kombinovanykh metodiv poverkhnevogo zmitsnennia detalei mashyn na osnovi neironnykh merezh i henetychnykh alhorytmiv [Modeling and optimization of combined methods of surface hardening of machine parts based on neural networks and genetic algorithms]. Tsentralnoukrainskyi naukovyi visnyk. Tekhnichni nauky, (13(44)), 274–285. https://doi.org/10.32515/2664-262X.2026.13(44).273-285 [in Ukrainian].
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