基于机器视觉法的结构表观损伤检测研究综述OA

Timely damage inspection is critical to ensuring structural safety.In recent years,computer vision,with its objectivity and efficiency,has become a core alternative to manual visual inspection.To systemati-cally review research progress and trends in this field,this paper presents an overview of computer vision-based structural surface damage inspection.It first summarizes common image acquisition devices,then introduces various damage recognition techniques,and elaborates on data bottlenecks in model training and corresponding solutions.It further discusses damage localization and quantification via 3D reconstruction,as well as damage condition assessment strategies integrating specifications,damage mechanisms,and data-driven methods.Finally,cutting-edge advances such as multimodal large language models are reviewed.Focusing on both engineering applications and the technical details and evolution of related algorithms,this pa-per provides a reference for intelligent structural inspection and assessment.