船用承压结构变形场混合数字孪生监测模型方法实现

Implementation of a mixed digital twin monitoring model for deformation field of marine pressure bearing structures

  • 摘要:
    目的 旨在为实现船舶的全生命健康监测设计一种面向结构健康监测的混合数字孪生系统。可实时采集及反馈关键舱室结构的变形,从而提升航运的信息化和安全管理能力。
    方法 首先,采用奇异值分解法对多组载荷形成的物理场信息进行数据压缩降维得到特定的标准正交基,创建基向量与载荷关系的响应面模型,输出基于实时输入载荷的有限元降阶模型。其次,采用基于地统计学的克里金插值算法,按照特定拓扑结构布点,将实时的传感器数据和降阶模型输出的补充点位数据经由卡尔曼滤波算法进行融合修正,共同计算监测对象的变形情况。最后,通过构建变形监测软硬件系统,实现监测物理特性的采集到可视化的全过程。
    结果 该系统在预设的载荷下,硬件采集系统能够稳定进行数据采集,配套的应用程序能够按照预期的要求进行实时可视化采集。
    结论 该结构健康混合数字孪生系统满足船舶的健康监测需求,对未来船舶的高度一体化、智能化发展具有一定的参考意义。

     

    Abstract:
    Objective This paper puts forward a hybrid digital twin monitoring system for structural health to realize the whole-life health monitoring of ships.
    Method The proposed model collects and feeds back the deformation of key cabin structures in real time in order to improve the information and safety management capabilities of shipping. The singular value decomposition method is used to compress and reduce the dimensions of the physical field information formed by multiple groups of loads to obtain the specific standard orthogonal basis, create the response surface model of the relationship between the basis vector and the load, and output a finite element reduced order model based on the real-time input load. The Kriging interpolation algorithm based on geostatistics is used to arrange points according to the specific topological structure, and the real-time sensor data and supplementary point data output by the reduced model are fused and corrected through the Kalman filter algorithm to jointly calculate the deformation of the monitored object. Finally, through the construction of a deformation monitoring software and hardware system, the whole process of physical characteristic collection and visualization is realized.
    Results Under the preset load, the hardware acquisition system can stably collect data while the supporting application program can visualize the acquisition process in real time according to the expected requirements.
    Conclusion The proposed structural health hybrid digital twin monitoring system meets the needs of ship health monitoring and has certain reference significance for the future development of highly integrated and intelligent ships.

     

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