基于图像的冷弯型钢剖面图三维表面重建

B. G. Erkal
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引用次数: 0

摘要

冷弯型钢(CFS)构件在建筑中的使用由于冷弯型钢研究的最新进展和开发的设计指南而显著增加。CFS建筑提供经济、轻便、高效和弹性的建筑系统。CFS构件是通过将薄钢板成形成几种不同的截面而得到的。由于运输、安装甚至生产,构成CFS构件的薄钢板上可能会出现几何缺陷。这些几何缺陷影响了CFS构件的预测物理响应。因此,为了有效地计算CFS构件的物理响应,有必要确定几何缺陷并研究其对构件行为的影响。本文提出了一种从二维图像中提取CFS构件三维表面数据的低成本方法,该方法可用于几何缺陷提取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image-based 3D surface reconstruction of cold-formed steel c-sections
The use of cold-formed steel (CFS) members in construction have increased significantly due to the recent advances in cold-formed steel research and the developed design guidelines. CFS construction provides affordable, light, efficient, and resilient building systems. CFS members are obtained by forming thin steel sheets into several different cross- sections. Due to transportation, installation, and even production, geometrical imperfections may occur on the thin steel sheets that form the CFS members. These geometrical imperfections affect the predicted physical response of CFS members. Thus, in order to efficiently compute the physical response of a CFS member, it is necessary to determine the geometric imperfections and investigate their effect on the member behavior. In this paper, a low cost methodology for extracting the 3D surface data of CFS members from 2D images that could be later used for geometric imperfection extraction is proposed.
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