Passive 3D motion optical data in shaking table tests of a SRG-reinforced masonry wall

Abstract

Unconventional computer vision and image processing techniques offer significant advantages for experimental applications to shaking table testing, as they allow the overcoming of most typical problems of traditional sensors, such as encumbrance, limitations in the number of devices, range restrictions and risk of damage of the instruments in case of specimen failure. In this study, a 3D motion optical system was applied to analyze shake table tests carried out, up to failure, on a natural-scale masonry structure retrofitted with steel reinforced grout (SRG). The system makes use of wireless passive spherical retro-reflecting markers positioned on several points of the specimen, whose spatial displacements are recorded by near-infrared digital cameras. Analyses in the time domain allowed the monitoring of the deformations of the wall and of crack development through a displacement data processing (DDP) procedure implemented ad hoc. Fundamental frequencies and modal shapes were calculated in the frequency domain through an integrated methodology of experimental/operational modal analysis (EMA/OMA) techniques with 3D finite element analysis (FEA). Meaningful information on the structural response (e.g., displacements, damage development, and dynamic properties) were obtained, profitably integrating the results from conventional measurements. Furthermore, the comparison between 3D motion system and traditional instruments (i.e., displacement transducers and accelerometers) permitted a mutual validation of both experimental data and measurement methods.

Historic Masonry Monitoring by Motion Magnification Analysis

“…4). The tested walls masonry, typical of central Italy, a region prone to earthquakes [8], [9]. On the left: lateral view with the safety framework, right: frontal view.…”

“…Then, the magnified intensity can be calculated as: (9) but eqn (9) is immediately derived from the first order Taylor's expansion of the exact magnified motion:…”

Processing of 3d Optical Motion Data of Shaking Table Tests: Filtering Optimization and Modal Analysis

“…Golay smoothing filter was considered, as it is one of the most effective algorithms in removing random noise from experimental data without excluding completely the contribution of frequencies higher than an upper cut-off limit [12]. It essentially performs a local polynomial regression on a series of equally spaced data points (windowing), to determine smoothed values [13].…”

Relative displacements of 3D optical markers for deformations and crack monitoring of a masonry structure under shaking table tests

“…This can be achieved in practice with the use of machine vision technologies [10]. In laboratory environment, for example, 3D motion capture systems [11] have been recently applied to shaking table tests with successful results both on scaled models [12][13] and on full-scale masonry structures [14].…”