Abstract

A novel method for structural health monitoring (SHM) by using RGB+D data has been recently proposed. RGB+D data are created by fusing image and laser scan data, where the D channel represents the distance, interpolated from laser scanner data. RGB channel represents image data obtained by an image sensor integrated in robotic total station (RTS) telescope, or on top of the telescope i.e., image assisted total station (IATS). Images can also be obtained by conventional cameras, or cameras integrated with RTS (different kind of prototypes). RGB+D image combines the advantages of the two measuring methods. Laser scans are used for distance changes in the line of sight and image data are used for displacements determination in two axes perpendicular to the viewing direction of the camera. Image feature detection and matching algorithms detect and match discrete points within RGB+D images obtained from different epochs. These way 3D coordinates of the points can be easily calculated from RGB+D images. In this study, the implementation of this method was proposed for measuring displacements and monitoring the behavior of structural elements under constant load in field conditions. For the precision analysis of the proposed method, displacements obtained from a numerical model in combination with measurements from a high precision linear variable differential transformer (LVDT) sensor was used as a reference for the analysis of determined displacements from RGB+D images. Based on the achieved results, we calculated that in this study, the precision of the image matching and fusion part of the RGB+D is ±1 mm while using the ORB algorithm. The ORB algorithm was determined as the optimal algorithm for this study, with good computing performance, lowest processing times and the highest number of usable features detected. The calculated achievable precision for determining height displacement while monitoring the behavior of structural element wooden beam under different loads is ±2.7 mm.

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