Abstract
The paper presents the results of operational reliability of electric locomotives of 2ES6 series belonging to Omsk operating locomotive depot of the West Siberian railway in 2020 according to the types of equipment faults. There is a comparative analysis of domestic and foreign studies concerning on-board systems of predictive technical diagnostics of electric rolling stock, providing control and technical condition of locomotives in real time. It is shown that the main direction of the improvement of on-board systems for predictive technical diagnostics of mainline freight electric locomotives is forecasting of electrical equipment service life on the basis of digital mathematical models of real-time objects taking into account retrospective and predictive descriptions of their behavior. The paper deals with the results of data analysis from on-board measuring systems of electric rolling stock by means of KNIME machine learning tool.
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DC electric freight locomotive 2ES6 with collector traction motors. Operation manual part 3. Description and operation of control and measurement system 2ES6.00.000.000.RE2. Yekaterinburg: “Ural Locomotives2”, 123 p
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Tretyakov, E., Solovyov, D., Kudinov, M. (2023). The Improvement of On-Board Systems for Predictive Technical Diagnostics of Mainline Electric Freight Locomotives Based on Digital Models. In: Guda, A. (eds) Networked Control Systems for Connected and Automated Vehicles. NN 2022. Lecture Notes in Networks and Systems, vol 510. Springer, Cham. https://doi.org/10.1007/978-3-031-11051-1_19
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DOI: https://doi.org/10.1007/978-3-031-11051-1_19
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