Özcan Barış, Schwermann Raimund, Blankenbach Jörg
Geodetic Institute and Chair for Computing in Civil Engineering & Geo Information Systems, RWTH Aachen University, Mies-van-der-Rohe-Str. 1, 52074 Aachen, Germany.
Materials (Basel). 2020 Dec 31;14(1):158. doi: 10.3390/ma14010158.
Determining the roughness of technical surfaces is an important task in many engineering disciplines. In civil engineering, for instance, the repair and reinforcement of building component parts (such as concrete structures) requires a certain surface roughness in order to ensure the bond between a coating material and base concrete. The sand patch method is so far the state-of-the-art for the roughness measurement of concrete structures. Although the method is easy to perform, it suffers from considerable drawbacks. Consequently, more sophisticated measurement systems are required. In a research project, we developed a novel camera‑based alternative, which comes with several advantages. The measurement system consists of a mechanical cross slide that guides an industrial camera over a surface to be measured. Images taken by the camera are used for 3D reconstruction. Finally, the reconstructed point clouds are used to estimate roughness. In this article, we present our measurement system (including the hardware and the self-developed software for 3D reconstruction). We further provide experiments to camera calibration and evaluation of our system on concrete specimens. The resulting roughness estimates for the concrete specimens show a strong linear correlation to reference values obtained by the sand patch method.
确定技术表面的粗糙度是许多工程学科中的一项重要任务。例如，在土木工程中，建筑构件（如混凝土结构）的修复和加固需要一定的表面粗糙度，以确保涂层材料与基础混凝土之间的粘结。到目前为止，砂铺法是混凝土结构粗糙度测量的最新技术。尽管该方法易于实施，但存在相当大的缺点。因此，需要更先进的测量系统。在一个研究项目中，我们开发了一种基于摄像头的新颖替代方法，它具有多个优点。该测量系统由一个机械横向滑板组成，它在待测量的表面上引导一台工业相机。相机拍摄的图像用于三维重建。最后，重建的点云用于估计粗糙度。在本文中，我们介绍了我们的测量系统（包括硬件和用于三维重建的自行开发的软件）。我们还提供了相机校准实验以及在混凝土试件上对我们系统的评估。混凝土试件的粗糙度估计结果与通过砂铺法获得的参考值显示出很强的线性相关性。
