DOI:
https://doi.org/10.14483/22484728.12790Publicado:
2017-06-28Número:
Vol. 11 Núm. 1 (2017)Sección:
Visión de CasoAnálisis de campos de esfuerzos utilizando fotoelasticidad visible e infrarroja
Stress field analysis using visible and infrared photoelasticity
Palabras clave:
Campos de esfuerzos, concentración de esfuerzos, descriptores de textura, fotoelasticidad digital, infrarrojo lejano (es).Palabras clave:
Stress field, stress concentration, texture descriptors, digital photoelasticity, far infrared (en).Descargas
Resumen (es)
Análisis de campos de esfuerzos en imágenes de fotoelasticidad son llevados a cabo mediante descriptores de textura en este artículo. En este caso, los descriptores considerados permiten identificar zonas con altas concentraciones de esfuerzo, incluso en casos con pérdida de contraste, los cuales son por lo general atribuidos a la baja resolución espacial de las franjas. De manera adicional, en este trabajo se analiza la variación en la densidad de franjas en términos de la longitud de onda. Esto último se hace extendiendo la generación de imágenes de fotoelasticidad en el infrarrojo lejano.
Resumen (en)
In this paper, stress fields analysis in photoelasticity digital images is carried out by using texture descriptors. In this case, such descriptors can identify zones with high stress concentration, even for cases with low spatial resolution in fringe patterns. In addition, this paper analyzes the variation that those fringes experience in function to wavelength. For this process, generating the photoelasticity images is extended to the far infrared.
Referencias
J. Quiroga y A. Gonzalez “Separation of isoclinics and isochromatics from photoelastic data with a regularized phase-tracking technique,” Applied optics, vol. 39, no. 17, 2000, pp. 2931–2940, https://doi.org/10.1364/AO.39.002931
M. Ragulskis y M. A. Sanjuan, “Chaotic pattern of unsmoothed isochromatics around the regions of concentrated stresses,” Computers & Graphics, vol. 32, no. 1, 2008, pp. 116–119, https://doi.org/10.1016/j.cag.2007.09.004
K. Ramesh, V. Ramakrishnan y C. Ramya, “New initiatives in single colour image-based fringe order estimation in digital photoelasticity,” The Journal of Strain Analysis for Engineering Design, vol. 50, no. 7, 2015, pp. 488–504, https://doi.org/10.1177/0309324715600044
W. D. Pilkey y D. F. Pilkey, “Peterson’s stress concentration factors”. John Wiley & Sons, 2008.
W. Shang, X. Ji, y X. Yang, “Study on several problems of automatic full-field isoclinic parameter measurement by digital phase shifting photoelasticity,” Optik-International Journal for Light and Electron Optics, vol. 126, no. 19, 2015, pp. 1981–1985, https://doi.org/10.1016/j.ijleo.2015.05.053
C. Magalhaes, P. Neto, P. Magalhaes, y C. de Barcellos, “Numerical methods for the photoelastic technique using phase shifting,” Journal of Mechanics, vol. 31, no. 4, 2015, pp. 355–367, https://doi.org/10.1017/jmech.2015.20
H. Fandiño, J. C. Briñez de León, A. Restrepo y J. W. Branch-Bedoya, “Texture analysis integrated to infrared light sources for identifying high fringe concentrations in digital photoelasticity,” in Applications of Digital Image Processing XL, vol. 10396. International Society for Optics and Photonics, p. 103962D
R. M. Haralick, K. Shanmugam et al., “Textural features for image classification,” IEEE Transactions on systems, man, and cybernetics, no. 6, 1973, pp. 610–621.
T. Kohonen, “The self-organizing map,” Neurocomputing, vol. 21, no. 1, 1998, pp. 1–6, https://doi.org/10.1016/S0925-2312(98)00030-7
T. Kohonen, “Essentials of the self-organizing map,” Neural networks, vol. 37, 2013, pp. 52–65, https://doi.org/10.1016/j.neunet.2012.09.018