Shenzhen Intercity Railway is an important transportation facility in the Guangdong-Hong Kong-Macao Greater Bay Area, which has the dual advantages of railway and subway. Due to the abundant rainfall and frequent typhoons in the Greater Bay Area, the flood control work of the intercity railway is crucial to the safety of passengers. At present, the railway and subway operation have accumulated a lot of experience in flood control work, and some lines are also equipped with digital flood control systems, which further improves the efficiency of the work. However, the design specification of the intercity railway flood control system has not yet been formulated, and a special scheme has to be designed in combination with the characteristics and needs of the project. In this paper, the dual characteristics of Shenzhen intercity railway are analyzed, and the risk points of flood control work are identified as station exit, station hall and platform, station pavilion, interval wastewater pumping house, and depot section area. Finally, a set of intelligent flood control system design scheme suitable for intercity railway scene is put forward. It can not only realize the effective monitoring of risk points, but also adopts multiple meteorological information, BIM and other technologies to further improve the intelligent decision-making level that is closely related to the quality of flood early warning, flood control drills and flood emergency command.


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    Title :

    Design of Intelligent Flood Control System for Shenzhen Intercity Railway


    Additional title:

    Mechan. Machine Science


    Contributors:
    Zhou, Kun (editor) / Jiang, Zhiwei (author) / Yan, Jijin (author) / Wang, Haibin (author)

    Conference:

    International Conference on Computational & Experimental Engineering and Sciences ; 2024 ; Singapore, Singapore August 03, 2024 - August 06, 2024



    Publication date :

    2024-08-21


    Size :

    7 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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