Structural Health Monitoring (SHM) has become increasingly critical due to the rapid deterioration of civil infrastructure. Traditional methods involving heavy equipment are costly and time-consuming. Recent SHM approaches use advanced non-contact sensors, IoT, and Augmented Reality (AR) glasses for faster inspections and immersive experiences during inspections. However, current methods lack quantitative damage data, remote collaboration support, and accurate 3D model alignment with the real structure. Recognizing these current challenges, this paper proposes an AR-based system that integrates Building Information Modelling (BIM) visualization and follows a flexible manipulation approach of 3D holograms to improve structural condition assessments. The proposed framework utilizes the Vuforia software development toolkit to enable the automatic alignment of 3D models to the real structure, ensuring successful model alignment to assist users in accurately visualizing damage locations. The framework also enables flexible manipulation of damage locations, making it easier for users to identify multiple damage points in the 3D models. The system is validated through lab-scale and full-scale bridge use cases, with data transfer performance analyzed under 4G and 5G conditions for remote collaboration. This study demonstrates that the proposed AR-based SHM framework successfully aligns 3D models with real structures, allowing users to manually adjust models and damage locations. The experimental results confirm its feasibility for remote collaborative inspections, highlighting significant improvements with 5G networks. Nevertheless, performance under 4G remains acceptable, ensuring reliability even without 5G coverage.

翻译：结构健康监测（SHM）因土木基础设施的快速劣化而日益重要。传统方法依赖重型设备，成本高昂且耗时。近期SHM方法采用先进非接触式传感器、物联网和增强现实（AR）眼镜，以实现快速检测和沉浸式巡检体验。然而，现有方法缺乏定量损伤数据、远程协作支持，以及三维模型与真实结构的精确对齐。针对这些挑战，本文提出一种基于AR的系统，集成建筑信息模型（BIM）可视化，并采用灵活的三维全息图操控方法，以改进结构状态评估。该框架利用Vuforia软件开发工具包实现三维模型与真实结构的自动对齐，确保模型成功配准，辅助用户精确可视化损伤位置。该框架还支持对损伤位置的灵活操控，使用户更易识别三维模型中的多个损伤点。系统通过实验室尺度及全尺寸桥梁案例验证，并在4G和5G条件下分析数据传输性能以评估远程协作能力。研究表明，所提出的基于AR的SHM框架成功实现了三维模型与真实结构的对齐，允许用户手动调整模型及损伤位置。实验结果证实了其在远程协同检测中的可行性，并凸显了5G网络带来的显著性能提升。尽管在4G网络下性能仍可接受，确保了无5G覆盖时的可靠性。