Research on and Assessment of the Reliability of Railway Transport Systems with Induction Motors

Oleg Gubarevych, Stanisław Duer, Inna Melkonova, Marek Woźniak (), Jacek Paś, Marek Stawowy, Krzysztof Rokosz, Konrad Zajkowski and Dariusz Bernatowicz
Additional contact information
Oleg Gubarevych: Department of Electromechanics and Rolling Stock of Railways, Kyiv Institute of Railway Transport of State University of Infrastructure and Technologies, 04071 Kyiv, Ukraine
Stanisław Duer: Department of Energy, Faculty of Mechanical Engineering, Technical University of Koszalin, 15-17 Raclawicka St., 75-620 Koszalin, Poland
Inna Melkonova: Department of Electrical Engineering, Volodymyr Dahl East Ukrainian National University, 91000 Kyiv, Ukraine
Marek Woźniak: Doctoral School, Technical University of Koszalin, 2 Sniadeckich St., 75-620 Koszalin, Poland
Jacek Paś: Faculty of Electronic, Military University of Technology of Warsaw, 2 Urbanowicza St., 00-908 Warsaw, Poland
Marek Stawowy: Department of Transport Telecommunication, Faculty of Transport, Warsaw University of Technology, 75 Koszykowa St., 00-662 Warsaw, Poland
Krzysztof Rokosz: Faculty of Electronic and Informatics, Technical University of Koszalin, 2 Sniadeckich St., 75-620 Koszalin, Poland
Konrad Zajkowski: Department of Energy, Faculty of Mechanical Engineering, Technical University of Koszalin, 15-17 Raclawicka St., 75-620 Koszalin, Poland
Dariusz Bernatowicz: Faculty of Electronic and Informatics, Technical University of Koszalin, 2 Sniadeckich St., 75-620 Koszalin, Poland

Energies, 2023, vol. 16, issue 19, 1-21

Abstract: Increasing the efficiency and reliability of modern railway transport is accompanied by an increase in monitoring and diagnostic systems for the current state of electric drives. Modern railway transport contains a large number of induction motors to ensure the operation of the drives of various mechanisms. In the article, based on the operational statistics of engine failures and the proposed scheme for diagnosing them, studies were carried out and a model was developed for assessing the reliability of a transport system equipped with an on-board diagnostic system for the current state. When building the models, the Markov method was used, including the construction of graphs for the five most relevant states of the induction electric motor during operation. The results obtained are relevant for evaluating the effectiveness of using the built-in diagnostic system and scheduling routine maintenance, which will affect the efficiency of railway transport. Based on the process of the diagnosis of railway transport systems with induction motors, five operating states of the object studied were interpreted: the state of full operation, state “S0”; the state of incomplete serviceability, state “S1”; critical serviceability, state “S2”; the state of the pre-damage condition, state “S3”; the state of unserviceability (defect), state “S4”. Subsequently, a five-state model of the operation process of railway transport systems with induction motors was developed. This model is also described by equations of state: Kolmogorov–Chapman equations. The reliability quantities determined form the basis for simulation reliability studies. The effect of the simulation study is the reliability quantities determined in the form of reliability functions and probabilities of the occurrences of the operating states of railway transport systems with induction motors; an important part of the reliability study of the system examined is to estimate the times of the occurrences in the object studied of the operating states in the future.

Keywords: induction motor; fault detection; transport equipment monitoring; on-board diagnostic system; reliability; servicing process; diagnostic process; diagnostic information (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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