Monitoring of Progressive Damage in Buildings Using Laser Scan Data

Abstract

ABSTRACT:Vulnerability of buildings to natural and man-induced hazards has become a main concern for our society. Ensuring their serviceability, safety and sustainability is of vital importance and the main reason for setting up monitoring systems to detect damages at an early stage. In this work, a method is presented for detecting changes from laser scan data, where no registration between different epochs is needed. To show the potential of the method, a case study of a laboratory test carried out at the Stevin laboratory of Delft University of Technology was selected. The case study was a quasi-static cyclic pushover test on a two-story high unreinforced masonry structure designed to simulate damage evolution caused by cyclic loading. During the various phases, we analysed the behaviour of the masonry walls by monitoring the deformation of each masonry unit. First a plane is fitted to the selected wall point cloud, consisting of one single terrestrial laser scan, using Principal Component Analysis (PCA). Second, the segmentation of individual elements is performed. Then deformations with respect to this plane model, for each epoch and specific element, are determined by computing their corresponding rotation and cloud-to-plane distances. The validation of the changes detected within this approach is done by comparison with traditional deformation analysis based on co-registered TLS point clouds between two or more epochs of building measurements. Initial results show that the sketched methodology is indeed able to detect changes at the mm level while avoiding 3D point cloud registration, which is a main issue in computer vision and remote sensing.

Concrete Preliminary Damage Inspection by Classification of Terrestrial Laser Scanner Point Clouds through Systematic Threshold Definition

“…By creating a 3D reference surface model from the points, rather than trying to detect deformation by single-point comparison, surface change is measured as the distance along the local surface normal [29,30]. Limitations of this approach include: (1) a specific surface model is needed for different applications with objects of specific geometric characteristics, Puente et al [31] detected damage on planar masonry walls by measuring cloud-to-plane distances between repeated laser scanning data and were able to detect changes at the noise level of individual laser scanner observations while avoiding 3D point cloud registration; (2) when deformation is derived by computing the differences between surface models fitted to different epochs, the estimated deformation field is basically one-dimensional [32,33]; (3) cloud-to-mesh approaches do not take into account the local orientation of the surface represented by the PCs [27]; and (4) meshing TLS data not only adds a level of error by interpolation, but can also create erroneous surfaces [22]. Additionally, meshing PCs have severe limitations specially for sophisticated historic structures presenting roughness at all scales [34].…”

Photogrammetric Solution for Analysis of Out-Of-Plane Movements of a Masonry Structure in a Large-Scale Laboratory Experiment

“…Examples of its applicability range from large civil infrastructures such as dams [1][2][3] or bridges [4][5][6]-even in a dynamic loading scenarios [7,8]-to laboratory specimens [9][10][11][12][13][14][15][16][17]. Within this context, the laser scanning technology is placed as the most used remote sensing approach [1][2][3]5,9,13] as it can directly provide high-density three-dimensional (3D) data in the form of point clouds. Through the use of these sensors, it is possible to evaluate the deformation suffered by a structure by means of different change detection methods, such as the radial basis approach [3,18], the plane-fitting method [9], or the curve-fitting strategy [19].…”

“…Within this context, the laser scanning technology is placed as the most used remote sensing approach [1][2][3]5,9,13] as it can directly provide high-density three-dimensional (3D) data in the form of point clouds. Through the use of these sensors, it is possible to evaluate the deformation suffered by a structure by means of different change detection methods, such as the radial basis approach [3,18], the plane-fitting method [9], or the curve-fitting strategy [19]. These approaches exploit data redundancy, providing better accuracy than the single-point measurement [19].…”

“…In addition to this, its measurement principle-based on the emission and reception of a laser beam-within the necessity of having a dense point cloud, requires the investment of several minutes to capture the whole scene. This issue restricts the use of this technology to those cases in which the structure is completely static [3,9,13,18,19].Another potential approach for the analysis of changes and deformation in structures that does not share this restriction is photogrammetry [4,[6][7][8][10][11][12]14,15,17,[20][21][22]. This approach, in contrast to laser scanning, is relatively low-cost as it is possible to obtain reliable results by means of common digital single-lens reflex (DSLR) cameras [6,15,16,21,22].…”

“…In addition to this, its measurement principle-based on the emission and reception of a laser beam-within the necessity of having a dense point cloud, requires the investment of several minutes to capture the whole scene. This issue restricts the use of this technology to those cases in which the structure is completely static [3,9,13,18,19].…”