A NEW DIGITAL IMAGE CORRELATION SOFTWARE FOR DISPLACEMENTS FIELD MEASUREMENT IN STRUCTURAL APPLICATIONS

Autor: R. Ravanelli, A. Nascetti, M. Di Rita, V. Belloni, D. Mattei, N. Nisticó, M. Crespi
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-4-W2, Pp 139-145 (2017)
Druh dokumentu: article
ISSN: 1682-1750
2194-9034
DOI: 10.5194/isprs-archives-XLII-4-W2-139-2017
Popis: Recently, there has been a growing interest in studying non-contact techniques for strain and displacement measurement. Within photogrammetry, Digital Image Correlation (DIC) has received particular attention thanks to the recent advances in the field of lowcost, high resolution digital cameras, computer power and memory storage. DIC is indeed an optical technique able to measure full field displacements and strain by comparing digital images of the surface of a material sample at different stages of deformation and thus can play a major role in structural monitoring applications. For all these reasons, a free and open source 2D DIC software, named py2DIC, was developed at the Geodesy and Geomatics Division of DICEA, University of Rome La Sapienza. Completely written in python, the software is based on the template matching method and computes the displacement and strain fields. The potentialities of Py2DIC were evaluated by processing the images captured during a tensile test performed in the Lab of Structural Engineering, where three different Glass Fiber Reinforced Polymer samples were subjected to a controlled tension by means of a universal testing machine. The results, compared with the values independently measured by several strain gauges fixed on the samples, demonstrate the possibility to successfully characterize the deformation mechanism of the investigated material. Py2DIC is indeed able to highlight displacements at few microns level, in reasonable agreement with the reference, both in terms of displacements (again, at few microns in the average) and Poisson’s module.
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