Improving tractor reliability through monitoring of air parameters in the engine intake system
References
- Ali, A. A. M., 2019. An innovative design of air filter in diesel engines of the tractors. International Journal of Mechanical and Production Engineering Research and Development (IJMPERD), 9(1), 541–544. Paper ID: IJMPERDFEB201952. https://www.researchgate.net/publication/330635628_an_innovative_design_of_air_filter_in_diesel_engines_of_the_tractors
- Angelucci, L., & Mattetti, M., 2024. The development of reference working cycles for agricultural tractors. Biosystems Engineering, 242, 29–37. DOI: 10.1016/j.biosystemseng.2024.04.004
- ASAE Standards D497.4, 1999. Agricultural machinery management data. American Society of Agricultural Engineers, St. Joseph, MI, USA.
- Babchenko, L. A., & Gulyarenko, A. A., 2020. Data control for reliability of agricultural tractors. Journal of Machinery Manufacture and Reliability, 49(10), 900–906. DOI: 10.3103/S10526 18820100039
- Balyasnikov, A. S., Gritsenko, A., Shepelev, V., Kaliyev, B. K., Kostyuchenkov, N., & Fadina, O., 2022. The development of methodological techniques and an algorithm for diagnosing modern in-take systems for internal combustion engines. FME Transactions, 50(2), 302–312. DOI: 10.5937/fme2201302B
- Barlow, R. E., & Hunter, L. C., 1960. Optimum preventive maintenance policies. Operations Research, 8(1), 90–100. DOI: 10.1287/opre.8.1.90
- Craessaerts, G., De Baerdemaeker, J., & Saeys, W., 2010. Fault diagnostic systems for agricultural machinery. Biosystems Engineering, 106(1), 26–36. DOI: 10.1016/j.biosystemseng. 2009.12.004
- Daly, P. D., & Vanderveen, J. K., 2002. Dust sensing assembly air in-take system (US Patent No. US6394062B2). Siemens Canada Ltd. https://patents.google.com/patent/US6394062B2/en
- Dhillon, B. S., 1989. Life cycle costing: Techniques, models and applications. Gordon and Breach Science Publishers, New York. DOI: 10.4324/9780203823682
- Ding, L., Cao, W., Wang, Y., Xu, C., Hao, R., Su, R., & Niraj, K., 2026. Wear particle dynamic concentration modeling and wear state prediction of cylinder liner piston lubrication system in internal combustion engine. Industrial Lubrication and Tribology, 78(2), 243–259. DOI: 10.1108/ILT-07-2025-0311
- Dziubak, T., & Kowalski, M., 2025. Problems of operating internal combustion engines in dusty conditions. Journal of KONBiN, 55(1), 61–82. DOI: 10.5604/01.3001.0055.0619
- Dziubak, T., & Dziubak, S. D., 2020. Experimental study of filtration materials used in the car air intake. Materials, 13(16), 3498. DOI: 10.3390/ma13163498
- Durczak, K., & Selech, J., 2022. The quantification of operational reliability of agricultural tractors with the competing risks method. Tehnički vjesnik, 29(2), 628–633. DOI: 10.17559/TV-20201118115902
- Fairuz, S. A., Chen, G., & Maraseni, T., 2026. Driving change in agriculture (2020–2025): A global review of LCA findings and adoption factors for agricultural electric vehicles. Renewable and Sustainable Energy Reviews, 226, 116295. DOI: 10.1016/j.rser.2025.116295
- Franchek, M. A., Buehler, P. J., & Makki, I., 2007. Intake air path diagnostics for internal combustion engines. Journal of Dynamic Systems, Measurement, and Control, 129(1), 32–40. DOI: 10.1115/1.2397150
- Gnanamalar, R. H., & Ayyasamy, R. K., 2025. Digital twin technology in smart agriculture: Enhancing productivity and sustainability. In Digital Twins for Smart Cities and Villages, 327–352. Elsevier. DOI: 10.1016/B978-0-443-28884-5.00015-4.
- Gulyarenko, A. A., 2018. Calculation method of the reasonable reliability level based on the cost criteria. Journal of Machinery Manufacture and Reliability, 47(1), 96–103. DOI: 10.3103/s1052618817060085
- Gulyarenko, A. A., Bembenek, M. J., Iskakov, R. M., Shaimuratova, E. S., & Gulyarenko, A. V., 2024. Development of a tractor reliability optimization model: A review of research and rationale for the components. Material and Mechanical Engineering Technology, (3), 54–61. DOI: 10.52209/2706-977X_2024_3_54
- Gulyarenko, A. A., Bembenek, M. J., Iskakov, R. M., Gulyarenko, A. V., Deshko, T. A., & Shaimuratova, E. S., 2025. Mathematical model of differentiation of tractor reliability indicators and its application for given conditions of an agricultural enterprise. Production Engineering Archives, 31(3), 394–400. DOI: 10.30657/pea.2025.31.36
- Gurtam. (n.d.). Wialon GPS tracking platform. Retrieved May 19, 2026, from https://wialon.com/
- Herranz-Matey, I., & Ruiz-Garcia, L., 2025. Agricultural tractor efficiency development as a sustainable model and evaluating the implementation of its automation operations: a case study. International Journal of Agricultural Sustainability, 23(1), 2546703. DOI: 10.1080/14735903.2025.2546703
- Jardine, A. K. S., Lin, D., & Banjevic, D., 2006. A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing, 20(7), 1483–1510. DOI: 10.1016/j.ymssp.2005.09.012
- Kadirov, S., & Muhametbaev, A., 2025. Increasing lifetime of motor tractor diesel engines and their fuel supply equipment in high dust air conditions. In AIP Conference Proceedings (Vol. 3256, No. 1, p. 060028). AIP Publishing LLC. DOI: 10.1063/5.0275318
- Kang, J., Shu, C., Yang, H., Liu, Y., Yan, C., & Zhang, F., 2025. Wear prediction of internal combustion engine cylinder liners based on adaptive generative adversarial networks. Results in Engineering, 27, 105740. DOI: 10.1016/j.rineng.2025.105740
- Khorshid, E. A., & Nawwar, A. M., 1991. A review of the effect of sand dust and filtration on automobile engine wear. Wear, 141(2), 349–371. DOI: 10.1016/0043-1648(91)90279-4
- Kirovsky Zavod Group. (n.d.). Official website of Kirovsky Zavod Group. https://kzgroup.ru/
- Komorska, I., Wołczyński, Z., & Borczuch, A., 2018. Fault diagnostics in air intake system of combustion engine using virtual sensors. Diagnostyka, 19(1), 25–32. DOI: 10.29354/diag/80972 Kuperus, J. B., Van Der Kooi, J. T., & De Wit, B. J., 2018. Air filter monitoring (RU Patent No. RU2664944C2). Koninklijke Philips N.V. https://patents.google.com/patent/RU2664944C2/en
- Li, D., Zheng, Y., & Zhao, W., 2019. Fault analysis system for agricultural machinery based on big data. IEEE Access, 7, 99136-99151. DOI: 10.1109/ACCESS.2019.2928973
- LLC Tehavtomatika. (n.d.). Escort TD-BLE fuel level sensor. Retrieved from https://t-a-e.ru/system_gps/1030/
- Pradel, M., 2023. Life cycle inventory data of agricultural tractors. Data in Brief, 48, 109174. DOI: 10.1016/j.dib.2023.109174
- Riegel, J., Kalman, J., & Jones, M., 2012. Optical embedded dust sensor for engine protection and early warning on M1 Abrams/ground combat vehicles. Proc. SPIE 8368, Photonic Applications for Aerospace, Transportation, and Harsh Environment III, 83680B (10 May 2012); https://doi.org/10.1117/12.918307
- Sherif, Y. S., & Smith, M. L., 1981. Optimal maintenance models for systems subject to failure-A review. Naval Research Logistics Quarterly, 28(1), 47–74. DOI: 10.1002/nav.3800280104
- Shykhmat, A., & Veres, Z., 2024. Agriculture Vehicles Predictive Maintenance With Telemetry, Maintenance History and Geo-spatial Data. Advances in Cyber-Physical Systems, 9(2), 134–139. DOI: 10.23939/acps2024.02.134
- Surendar, V., Hussain, S. K., Muthusamy, S., Kiruthika, G., Karthik, P., & Meiyappan, S. R., 2025. GPS-based tractor tracking and monitoring system. In 2025 6th International Conference on Electronics and Sustainable Communication Systems (ICESC), 385–391. IEEE. DOI: 10.1109/ICESC65114.2025.11212307
- Tavoda, P., Kovac, J., & Lukaszczyk, Z., 2018. Reliability analysis of forest machines due to FMEA method. Management Systems in Production Engineering, 26(4), 200–206. DOI: 10.1515/mspe-2018-0032
- Teltonika IoT Group. (n.d.). Teltonika GPS tracking devices. Retrieved from https://www.teltonika-gps.com/products/trackers/basic/fmb920
- Teng, D., Sa, X., Wang, J., Zhao, T., Wang, J., & Zhu, J., 2026. Friction and wear behaviors of sliding bearing under heavy loads and simulated sand-dust conditions. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology. OnlineFirst. DOI: 10.1177/13506501261426736
- Teplicka, K., & Stasa, P., 2026. The proactive maintenance strategy and its impact on the performance in public transport. Management Systems in Production Engineering, 34(2), 282–289. DOI: 10.2478/mspe-2026-0028
- Toma, M., & Fileru, I. F., 2016. Research on the air filters’ maintenance for diesel engines. Procedia Technology, 22, 969–975. DOI: 10.1016/j.protcy.2016.01.119
- Versatile. (n.d.). Official website of Versatile Tractors. https://www.versatile-ag.com
- Wiercioch, J., 2024. Hybrid predictive maintenance model – study and implementation example. Production Engineering Archives, 30(3), 285–295. DOI: 10.30657/pea.2024.30.28.
- Wittbrodt, P., 2026. Algorithmic approach to prescriptive maintenance in Industry 4.0. Production Engineering Archives, 32(1), 123–135. DOI: 10.30657/pea.2026.32.11
- Yin, J., Chen, Z., Lv, S., Wu, H., Gao, Y., & Wu, L., 2024. Design and fatigue life analysis of the rope-clamping drive mechanism in a knotter. Agriculture, 14, 1254. DOI: 10.3390/agriculture 14081254
- Zhang, C., Song, J., Yin, X., Cai, J., Liang, Y., & Lu, J., 2025. Digital twin-based approaches for agricultural machinery damage prediction and maintenance: A review. Journal of Computational Design and Engineering, 12(10), 87–117. DOI: 10.1093/jcde/qwaf097
Language: English
Page range: 502 - 512
Submitted on: May 14, 2026
Accepted on: Sep 3, 2026
Published online: Oct 25, 2026
Published in print: Dec 1, 2026
Published by: Quality and Production Managers Association
In partnership with: Paradigm Publishing Services
Keywords:
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© 2026 Alexandr Gulyarenko, Ruslan Iskakov, Anna Gulyarenko, Tatyana Deshko, Elmira Shaimuratova, Michał Bembenek, published by Quality and Production Managers Association
This work is licensed under the Creative Commons Attribution 4.0 License.