The in-vehicle network communication system and the in-vehicle network control system are independent and inseparable, and the network performance and control performance affect and restrict each other. The purpose of this paper is to study the optimal design of a network control system for railway vehicles based on artificial intelligence. This article is a project actually implemented relying on the railway vehicle network control system in M province. This paper selects the MVB network that conforms to the IEC61375-3 standard through the analysis and comparison of several mainstream communication networks in the rail transit industry. In the process of network topology design, the network system is divided into two network segments, the vehicle network and the train network, through the rational use of repeaters. There are a total of 160 CCU source ports and sink ports. In the process of designing the network control system, we have fully considered various redundancy design schemes, such as master control redundancy, line redundancy, key signal redundancy, hard cable signal redundancy, etc., to ensure the stability and reliability of the entire system. In order to achieve the design goal of subway vehicles mainly based on network control and supplemented by hard line control.


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    Titel :

    Railway vehicle network control system based on artificial intelligence


    Beteiligte:
    Huang, Letian (Herausgeber:in) / Gao, Shuang (Autor:in)

    Kongress:

    2022 Workshop on Electronics Communication Engineering ; 2022 ; Xi'an, China


    Erschienen in:

    Proc. SPIE ; 12720


    Erscheinungsdatum :

    28.06.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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