Abstract
This work considers the indicators that affect the state of the traction electric motor of electric rolling stock and are used for predictive diagnostics as part of an intelligent system for managing the production resources of urban rail transport systems in solving the following tasks: assessing the condition of a vehicle’s equipment, predicting its operability, and deciding on the need for unscheduled inspection and repairs; improving the process of scheduling the turnover of rolling stock and its adaptation under dynamically variable conditions; and improving the efficiency of electric rolling stock control, namely, increasing the level of efficiency and reducing the likelihood of unscheduled repairs and the amount of repair costs. A variant of using the parameters of armature current as an indicator, affecting the condition of the traction motor of electric rolling stock, is proposed. The condition of the traction motor is assessed by comparing sections on which unscheduled repairs are performed and those that do not undergo any such repairs. A review of predictive diagnostics systems used in railroad transport for locomotives is carried out.
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Funding
This work was supported by the Russian Foundation for Basic Research, Sirius University, OAO RZD, and Talent and Success Education Fund, project no. 20-37-51001
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Translated by S. Kuznetsov
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Sidorenko, V.G., Kulagin, M.A. & Mikhailov, S.V. Approach to Predicting Failures of Traction Electric Motors. Russ. Electr. Engin. 93, 592–595 (2022). https://doi.org/10.3103/S1068371222090139
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DOI: https://doi.org/10.3103/S1068371222090139