In response to the issue of limited timeliness in the current monitoring of ship anchor dragging, a method of early warning of ship anchor dragging risk utilising fuzzy set theory was proposed. Based on sailing simulator, ship anchoring simulation experiments were conducted to collect trajectory data of ship anchoring under various environmental conditions, and the characteristics of the trajectory of normal anchored ships were analyzed. During a yawing motion, the yawing width, ground speed and heading change rate of were established as early warning indicators for ship anchor dragging risk. Triangular fuzzy numbers and the distribution of early warning indicators obtained from simulation experiments were combined to determine the membership functions of each indicator, and the entropy weight method was used to determine indicator weights. Then ship anchor dragging risk was comprehensively evaluated and the anchor dragging probability was quantified. Warning levels were set according to actual conditions, and the warnings will be alarmed if the anchor dragging probability reaches the corresponding warning level. The results indicate that during the yawing motion of anchored ships, larger yawing width, higher ground speed, and smaller ship heading change rate correspond to higher anchor dragging probability. Finally, sailing simulators were utilized for simulation experiments ,and the feasibility of the proposed method was validated. The method exhibits practical operability and demonstrates favorable timeliness in early warning capabilities.


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    Titel :

    Risk early warning method of ship anchor dragging based on simulation experiments


    Beteiligte:
    Shangguan, Wei (Herausgeber:in) / Wu, Jianqing (Herausgeber:in) / Chen, Pengjie (Autor:in) / Xi, Yongtao (Autor:in) / Han, Jiang (Autor:in)

    Kongress:

    Third International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2023) ; 2023 ; Xi'an, China


    Erschienen in:

    Proc. SPIE ; 12989


    Erscheinungsdatum :

    09.04.2024





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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