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Strain Measurement of Medical Textile Using 2D Digital Image Correlation Method

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Experimental and Computational Investigations in Engineering (CNNTech 2020)

Abstract

Medical textile plays an important role in the technical textiles sector as one of the most rapidly growing sectors in the technical textile market. The textile materials should have some adequate mechanical properties to be useful as medical textile. Tensile strength presents one of the basic mechanical properties used to describe textile specimens. Standardized tensile testing procedures on textile specimens were commonly used in the past. The aim of this paper was to measure in-plane strain field on the tensile medical textile specimen using 2D Digital Image Correlation method (2D-DIC). 2D-DIC is a non-contact optical method for accurate displacement and strain full-field measurement. In this study, two medical cotton textiles, with density 120 and 130 g/m2, were used to create three specimens for each material. Each specimen was placed in the tensile testing machine and measured until the break. During the tensile testing, camera was automatically recording full-field displacement in X and Y directions. Textile 1 and Textile 2 showed significant differences in point distance values, despite the small deviation in densities (less than 10%). Mean value of the elongation for Textile 1 is more than a double than the elongation for Textile 2, although the difference for mean value of Maximum force if negligible. Also, it has been showed that 2D-DIC can play significant role for measurement in textile mechanical properties measurement.

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Acknowledgement

This research was supported by Ministry of Education, Science and Technological Development of Republic of Serbia under Project TR35031.

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Correspondence to Nenad Mitrovic .

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Mitrovic, N., Mitrovic, A., Reljic, M. (2021). Strain Measurement of Medical Textile Using 2D Digital Image Correlation Method. In: Mitrovic, N., Mladenovic, G., Mitrovic, A. (eds) Experimental and Computational Investigations in Engineering. CNNTech 2020. Lecture Notes in Networks and Systems, vol 153. Springer, Cham. https://doi.org/10.1007/978-3-030-58362-0_26

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