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International Scientific Siberian Transport Forum

TransSiberia 2019: VIII International Scientific Siberian Transport Forum pp 427–442Cite as

Actual Artificial-Intelligence Based System for Assessment of the Technical State of the Rolling Stock Fleet

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1115))

Abstract

The goal of the work is to development of a synchronous-replicated model for the assessment of the technical state of a locomotive as a technological system. When performing the work, method of systems analysis, computer and mathematical modelling, artificial intelligence, and mathematical analysis were used. As a result of the research we have obtained a mathematical synchronous-replicated model for the assessment of the technical state of a locomotive based on multilayer neuron forecasting network. The model developed can be used in systems for monitoring, controlling and diagnosing the technical state of the locomotive fleet. This model possesses such novel specific features as low sampling period between quizzing of monitoring facilities, versatility, adaptability and operability. This suggested model resolves a range of tasks set forth in the Concept for the development of the OJSC Russian Railways connected with the implementation of an actual system for repairs and maintenance according to the current condition of locomotives as well as the digitalization of the advanced fields of the company.

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Author information

Authors and Affiliations

  1. Far Eastern State Transport University, Seryshev st., 47, Khabarovsk, 680021, Russia

    Artyom Plyaskin & Alexey Kushniruk

Authors
  1. Artyom Plyaskin
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  2. Alexey Kushniruk
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Corresponding author

Correspondence to Alexey Kushniruk .

Editor information

Editors and Affiliations

  1. Department of Roads, Airports and Railways, University of Belgrade, Belgrade, Serbia

    Zdenka Popovic

  2. Siberian Transport University, Novosibirsk, Russia

    Aleksey Manakov

  3. Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia

    Vera Breskich

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Plyaskin, A., Kushniruk, A. (2020). Actual Artificial-Intelligence Based System for Assessment of the Technical State of the Rolling Stock Fleet. In: Popovic, Z., Manakov, A., Breskich, V. (eds) VIII International Scientific Siberian Transport Forum. TransSiberia 2019. Advances in Intelligent Systems and Computing, vol 1115. Springer, Cham. https://doi.org/10.1007/978-3-030-37916-2_42

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  • DOI: https://doi.org/10.1007/978-3-030-37916-2_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37915-5

  • Online ISBN: 978-3-030-37916-2

  • eBook Packages: EngineeringEngineering (R0)

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