Hajjar Mohammad, Zappa Emanuele, Bolzon Gabriella
Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy.
Department of Mechanical Engineering, Politecnico di Milano, Via Privata Giuseppe La Masa 1, 20156 Milan, Italy.
Sensors (Basel). 2025 Aug 19;25(16):5134. doi: 10.3390/s25165134.
The structural health monitoring (SHM) of existing infrastructure and heritage buildings is essential for their preservation and safety. This is a review paper which focuses on modern three-dimensional (3D) measurement techniques, particularly those that enable the assessment of the structural response to environmental actions and operational conditions. The emphasis is on the detection of fractures and the identification of the crack geometry. While traditional monitoring systems-such as pendula, callipers, and strain gauges-have been widely used in massive, quasi-brittle structures like dams and masonry buildings, advancements in non-contact and computer-vision-based methods are increasingly offering flexible and efficient alternatives. The integration of drone-mounted systems facilitates access to challenging inspection zones, enabling the acquisition of quantitative data from full-field surface measurements. Among the reviewed techniques, digital image correlation (DIC) stands out for its superior displacement accuracy, while photogrammetry and time-of-flight (ToF) technologies offer greater operational flexibility but require additional processing to extract displacement data. The collected information contributes to the calibration of digital twins, supporting predictive simulations and real-time anomaly detection. Emerging tools based on machine learning and digital technologies further enhance damage detection capabilities and inform retrofitting strategies. Overall, vision-based methods show strong potential for outdoor SHM applications, though practical constraints such as drone payload and calibration requirements must be carefully managed.
对现有基础设施和历史建筑进行结构健康监测（SHM）对于它们的保护和安全至关重要。这是一篇综述论文，重点关注现代三维（3D）测量技术，特别是那些能够评估结构对环境作用和运行条件响应的技术。重点在于裂缝的检测和裂纹几何形状的识别。虽然传统监测系统，如摆锤、卡尺和应变仪，已广泛应用于大坝和砖石建筑等大型准脆性结构，但非接触式和基于计算机视觉的方法的进步正越来越多地提供灵活高效的替代方案。无人机搭载系统的集成便于进入具有挑战性的检查区域，能够从全场表面测量中获取定量数据。在所综述的技术中，数字图像相关（DIC）因其卓越的位移精度而脱颖而出，而摄影测量和飞行时间（ToF）技术提供了更大的操作灵活性，但需要额外处理以提取位移数据。收集到的信息有助于数字孪生的校准，支持预测性模拟和实时异常检测。基于机器学习和数字技术的新兴工具进一步增强了损伤检测能力，并为修复策略提供依据。总体而言，基于视觉的方法在户外结构健康监测应用中显示出强大的潜力，不过必须仔细管理无人机载荷和校准要求等实际限制因素。
