发表机构
University of Virginia（弗吉尼亚大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出两种互补非接触视觉方法，结合激光扫描与3D-DIC、拓扑优化技术，可检测量化结构的可见与亚表面缺陷，为结构状态评估提供高保真方案。
AI 中文摘要
结构缺陷的可靠表征需要能够同时分辨直接可观测的表面损伤与从 inspected 表面不可见的损伤的方法。本研究提出两种互补的非接触式、基于视觉的结构部件缺陷检测与定量表征方法。第一种方法采用高分辨率激光扫描生成受损钢试样的三维（3D）点云，对实测点云与参考点云进行对比处理，以定位受损区域、量化几何损失，并将实测缺陷几何转换为有限元表示。第二种方法将采用三维数字图像相关（3D-DIC）获得的全场表面变形测量结果与有限元模型更新及拓扑优化相结合；在该逆框架中，实测表面响应通过对结构响应空间分布的影响来推断亚表面异常。研究采用含受控光滑缺陷与随机分布缺陷的实验钢梁试样对上述方法进行评估，与基于铣削的真实值测量结果对比表明，两种方法均可识别并量化缺陷几何，同时为可见与亚表面损伤评估提供互补信息。该组合框架为具有复杂不规则损伤的部件实现高保真非接触结构状态评估及模型更新开辟了途径。
英文摘要
Reliable characterization of structural defects requires methods capable of resolving both directly observable surface damage and damage that is not visible from the inspected surface. This study presents two complementary non-contact, vision-based approaches for the detection and quantitative characterization of defects in structural components. The first approach employs high-resolution laser scanning to generate three-dimensional (3D) point clouds of damaged steel specimens. Comparative processing of measured and reference point clouds is used to localize damaged regions, quantify geometric loss, and transfer the measured defect geometry to a finite element representation. The second approach combines full-field surface deformation measurements obtained using three-dimensional digital image correlation (3D-DIC) with finite element model updating and topology optimization. In this inverse framework, measured surface response is used to infer subsurface abnormalities through their influence on the spatial distribution of structural response. Experimental steel-beam specimens containing controlled smooth defects and randomly distributed defects are used to evaluate the approaches. Comparisons with milling-based ground-truth measurements demonstrate that both methods can identify and quantify defect geometry, while providing complementary information for visible and subsurface damage assessment. The combined framework establishes a pathway toward high-fidelity, non-contact structural condition assessment and model updating for components with complex and irregular damage.
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