Prospects for monitoring engine oil performance in mining dump trucks

DOI: https://doi.org/10.30686/1609-9192-2025-5-160-166

Читать на русскоя языкеM.S. Nikitenko , D.Yu. Khudonogov, M.V. Efremenkova
Federal Research Center of Coal and Coal Chemistry of Siberian Branch of the Russian Academy of Sciences, Kemerovo, Russian Federationn
Russian Mining Industry №5 / 2025 p. 160-166

Abstract: The object of the study is the method for assessing the current condition of mining dump truck engines based on analyzing the degree of engine oil degradation. The subject of the study is the functionality of the developed hardware and software to monitor the performance of engine oil based on the quantitative analysis of the operational data. The problem lies in the low efficiency of the laboratory methods for analyzing the characteristics of used engine oil during operation. It requires the development of technologies for continuous monitoring of the engine oil performance parameters and ensuring the reduction of unscheduled downtime of the equipment due to timely prevention of emergency operation of the mining vehicle engines. The main objective of the study was to develop a hardware and software suite for monitoring the performance of oil and assess the compliance of the obtained quantitative data with the results of laboratory studies and real operating modes of the unit under operating conditions. The work uses dielectric and spectral methods to analyze engine oil samples. Based on the results of analyzing a set of operational samples of engine oil using various methods, a conclusion was made about the compliance of the obtained quantitative data with the content of the oil degradation marker elements, which are Al, Cu, Fe, Na, Pb and Si. A conclusion is made about the unevenness of oil degradation and its dependence on the technical condition of a specific engine. The results of analyzing the operational data are shown for the monitoring system installation on the unit, in particular the possibility of recording abrupt changes in the condition of the engine oil in real time. The advantages are formulated of the development and implementation of the hardware and software suite for monitoring the oil performance and analyzing the data obtained to prevent unscheduled downtime through the timely performance of the service and repair work.

Keywords: mining machines, mining dump truck, engine, engine oil, motor oil, express analysis, monitoring system, automated control system, technical diagnostics, downtime reduction

Acknowledgements: The work was carried out within the framework of the state assignment of the Federal Research Center for Coal and Coal Chemistry of the Siberian Branch of the Russian Academy of Sciences, project FWEZ-2024-0025 “Development of scientific foundations for the creation of autonomous and military mining machines, equipment, technical and control systems based on promising digital and robotic technologies (prolongation)”. (reg. No.125013101207-7).

For citation: Nikitenko M.S., Khudonogov D.Yu., Efremenkova M.V. Prospects for monitoring engine oil performance in mining dump trucks. Russian Mining Industry. 2025;(5):160–166. (In Russ.) https://doi.org/10.30686/1609-9192-2025-5-160-166

Article info

Received: 25.06.2025

Revised: 03.08.2025

Accepted: 04.08.2025

Information about the authors

Mikhail S. Nikitenko – Cand. Sci. (Eng.), Head of laboratory, Federal Research Center of Coal and Coal-Chemistry of Siberian Branch of the Russian Academy of Sciences, Kemerovo, Russian Federation; https://orcid.org/0000-0001-8752-1332 ; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Danila Yu. Khudonogov – Scientific Researcher, Federal Research Center of Coal and Coal-Chemistry of Siberian Branch of the Russian Academy of Sciences, Kemerovo, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Margarita V. Efremenkova – Engineer, Federal Research Center of Coal and Coal-Chemistry of Siberian Branch of the Russian Academy of Sciences, Kemerovo, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

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