大模型驱动的船舶结构健康监测系统关键技术研究综述及展望

Review and prospects of key technologies for large model-driven ship structural health monitoring systems

  • 摘要: 船舶结构健康监测系统是保障船舶安全运行的关键技术,将大模型技术与船舶结构健康监测深度融合可以有效提高监测效率与精度,故须梳理该系统涉及关键技术的发展现状,分析现存技术问题,并对未来发展方向提出展望。首先,系统梳理典型场景下的船用传感器技术、面向虚实融合的测点布局规划技术、数据降噪和补偿技术以及船舶应力重构与载荷反演技术的研究现状;同时,结合大模型在特征提取、多模态融合分析、自主学习等优势,针对性地提出大模型驱动的船舶结构健康监测系统的发展方向。然后,分析现存技术所面临的挑战:船用传感器网络的监测稳定性与适用性仍有待提高;现有测点布局方案对于多物理量的协同监测能力不足,企鹅测点布局方案设计缺乏有效的优化算法;数据降噪和补偿技术的实时计算效率和计算精度有限;应力分布重构与载荷反演技术在长期真实复杂海况下的准确性仍需进一步验证。最后,对该系统的未来发展方向提出展望,可重点突破船用传感器自诊断系统与测点布局智能优化,大模型驱动的多模态数据实时处理与多船型技术迁移,基于物理内核的船体结构响应智能反演与数字孪生平台开发等3个方向的技术难题,用以为船舶全生命周期结构安全提供更有力的保障。

     

    Abstract: The ship structural health monitorin system serves as a critical technology for ensuring vessel operational safety. The deep integration of large-scale models with structural health monitoring can significantly enhance monitoring efficiency and accuracy. This paper systematically reviews the state-of-the-art of key technologies in this field, analyzes existing technical challenges, and proposes future development directions to facilitate advancements in structural health monitoring systems. This study systematically reviews research progress in marine sensor technology for typical scenarios, virtual-physical fusion-based measurement point layout planning technology, data denoising and compensation technology, as well as ship stress reconstruction and load inversion technology. By leveraging the advantages of large models in feature extraction, multimodal fusion analysis, and autonomous learning, it proposes targeted future development directions for ship structural health monitoring systems. Current research shows that while the four key technologies of ship structural health monitoring systems have made progress, they still face numerous challenges. The monitoring stability and applicability of marine sensor networks need improvement; existing measurement point layout schemes demonstrate insufficient capability for multiphysics collaborative monitoring and lack effective optimization algorithms; data denoising and compensation technologies have limitations in real-time computational efficiency and accuracy; and the reliability of stress distribution reconstruction and load inversion technologies under long-term real complex sea conditions requires further verification. Future development should prioritize three key technical breakthroughs: intelligent self-diagnostic systems and optimized measurement point layouts for marine sensors, large model-driven real-time multimodal data processing and multi-ship-type technology transfer, and physics-informed intelligent inversion coupled with digital twin platform development. These advancements will provide enhanced structural safety assurance throughout a vessel's entire lifecycle.

     

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