In large-span grid structures with thousands of members involved, bending deformation of members is one of the most commonly observed damages affecting the normal service, even the safety of structures. Traditional testing and monitoring methods show weakness in the accurate judgment of crooked members and precision of deformation measurements. In this paper, a new deformation inspection and monitoring method of grid structures using image-based 3D reconstruction is proposed, wherein a new method is put forward to automatically recognize and extract the shape deformation of the structural member for the first time. First, the key area with multiple members is modeled as a three-dimensional mesh model using image-based 3D reconstruction. Then, a new automated recognition and extraction algorithm of shape deformation (AREAS) is carried out, and crooked members, together with their deformed shapes, are extracted from the mesh model through AREAS. In this study, a load experiment of a quadrangular pyramid grid structure containing artificial crooked members and speckled members is designed to compare the deformation measurements using image-based 3D reconstruction with those using laser scanning. The comparison of deformation and deformation increment shows an average error within 1 mm for image-based 3D reconstruction, which validates the proposed method in on-site inspection and monitoring.

中文翻译：

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网格结构中构件变形的自动检查和监测

在涉及数千个构件的大跨度网架结构中，构件的弯曲变形是影响正常使用甚至结构安全的最常见的损伤之一。传统的测试和监测方法在弯曲构件的准确判断和变形测量的精度方面存在弱点。本文提出了一种基于图像3D重建的网格结构变形检测与监测新方法，首次提出了一种自动识别和提取结构构件形状变形的新方法。首先，使用基于图像的 3D 重建将具有多个成员的关键区域建模为三维网格模型。然后，进行了一种新的形状变形自动识别和提取算法（AREAS），通过 AREAS 从网格模型中提取弯曲构件及其变形形状。在这项研究中，设计了一个包含人造弯曲构件和斑点构件的四棱锥网格结构的载荷实验，以比较使用基于图像的 3D 重建与使用激光扫描的变形测量​​。变形和变形增量的比较表明基于图像的 3D 重建的平均误差在 1 mm 以内，这验证了所提出的方法在现场检查和监测中的有效性。设计了一个包含人造弯曲构件和斑点构件的四棱锥网格结构的载荷实验，以比较使用基于图像的 3D 重建与使用激光扫描的变形测量​​。变形和变形增量的比较表明基于图像的 3D 重建的平均误差在 1 mm 以内，这验证了所提出的方法在现场检查和监测中的有效性。设计了一个包含人造弯曲构件和斑点构件的四棱锥网格结构的载荷实验，以比较使用基于图像的 3D 重建与使用激光扫描的变形测量​​。变形和变形增量的比较表明基于图像的 3D 重建的平均误差在 1 mm 以内，这验证了所提出的方法在现场检查和监测中的有效性。