Publication:
Determinación por Visión Artificial del Factor de Degradación en Aleaciones Biocompatibles

Thumbnail Image
Files
View Statistics
Reference Managers
Mendeley
Indexers
Google Scholar CORE
QR Code
QR Code
Authors

Authors

MEJIA MORALES, AURA SOFIA
Bautista Ruiz, Jorge H
Aperador Chaparro, Willian
Abstract (Spanish)
Se determinó por visión artificial el factor de degradación de una aleación biocompatible, AISI 316LVM. Para ello, se utilizó una solución fisiológica simulada (solución de Hanks), electrolito que simula la composición presente en el organismo, es decir, el ambiente donde el implante se utilizará. El comportamiento electroquímico fue evaluado mediante curvas potencio-dinámicas. La caracterización superficial se desarrolló mediante un estereoscopio y los productos de corrosión se evaluaron mediante difracción de rayos X. El sistema usó una imagen microscópica de la superficie del material en su estado natural (brillo espejo) como parámetro base para la comparación, para definir en qué estado se encuentran las muestras una vez han pasado por las pruebas realizadas. Se encontró, que es posible estimar el factor de degradación o de deterioro en un material mediante un análisis topográfico del mismo.
Abstract (English)
The degradation factor of a biocompatible alloy, AISI 316LVM, was determined by computer vision. For this, a simulated physiological solution (Hanks' solution) which simulates the electrolyte composition in the body, that is the environment in which the implant is used. The electrochemical behavior was evaluated by potentio-dynamic curves. The surface characterization was performed using a stereoscope and corrosion products were evaluated by X-ray diffraction. The system used a microscopic image of the surface of the material in its natural state (mirror finish) as a basis for comparison parameter to define what state are once samples have undergone testing. It was found that it is possible to estimate the factor of degradation or deterioration of a material through a topographic analysis
Extent
12 páginas
URI: https://repositorio.escuelaing.edu.co/handle/001/3299
Collections

Collections

AK - Diseño Sostenible en Ingeniería Mecánica – DSIM
References

Bonfield, W., Mechanical properties of bone. Biomaterials, 2, 251-252 (1981)

Bou-Saleh, Z., Shahryari, A. y Omanovic, S. Enhancement of corrosion resistance of a biomedical grade 316LVM stainless steel by potentiodynamic cyclic polarization. Thin Solid Films, 515, 4727-4737 (2007).

Bordji, K. y otros siete autores. Cytocompatibility of Ti-6Al-4V and Ti-5Al-2.5Fe alloys according to three surface treatments, using human fibroblasts and osteoblasts. Biomaterials, 17, 929-940 (1996).

Brune, D., y Hultquist G. Corrosion of a stainless steel with low nickel content under static conditions, Biomaterials, 6, 265-268 (1985).

Chmiel, M., Słowiński, M. y Dasiewicz, K., Application of computer vision systems for estimation of fat content in poultry meat, Food Control, 22(8), 1424-1427 (2011)

Cook, S.D., The in vivo performance of 250 internal fixation devices; a fellow up study, Biomaterials, 8, 177- 184 (1986).

De Mello, J.D.B. y De S. Balsamo, P.S., Comportamiento Tribológico de Aceros Inoxidables para Cubertería, Información Tecnológica, 17 (6), 57-62 (2006)

Dutta, S., Das, A., Barat, K., y Himadri, R. Automatic characterization of fracture surfaces of AISI 304LN stainless steel using image texture analysis, Measurement , 45, 1140–1150 (2012).

Geetha, M. y otros dos autores, Ti based biomaterials, the ultimate choice for orthopaedic implants, Progress in Materials Science, 54, 397-425 (2009)

German, S., Brilakis, I. y DesRoches, R. Rapid entropy-based detection and properties measurement of concrete spalling with machine vision for post-earthquake safety assessments, Advanced Engineering Informatics, 26, 846–858 (2012).

Infaimon, C., Visión artificial aplicada a la industria (2010), http://www.jcee.upc.es/JCEE2010/pdf_ponencies/PDFs/25_11_10/INFAIMON-Vision%20artificial.pdf. Acceso: 27 de agosto (2012

Jacobs, J. y otros seis autores, J. Clinical Orthopedics and Related Research, 358, 1999, 173-180 (1999

Langer, R., Cima, L.G., Tamada, J.A. y Wintermantel, E. Future directions in biomaterials, Biomaterials, 11, 738-745 (1990).

López, D.A., Durán, A. y Ceré, S., Caracterización superficial de acero inoxidable AISI 316L en contacto con solución fisiológica simulada, Actas del Congreso CONAMET/SAM, 256-260, La Serena, Chile, 3 al 5 de noviembre (2004).

Moreda, G.P., Muñoz, M.A., Ruiz-Altisent, M. y Perdigones, A., Shape determination of horticultural produce using two-dimensional computer vision – A review, Journal of Food Engineering, 108(2), 245-261 (2012).

Park, J.B. The Biomedical Engineering Handbook, 2a edición, 45-56. CRC Press, USA (1999)

Pourbaix, M. Electrochemical corrosion of metallic biomaterials, Biomaterials, 5, 122-134 (1984)

Rojas, T.V., Sanz, W. y Arteaga, F. Sistema de visión por computadora con la transformada de Hough. revista ingeniería UC, 15(1), 77-87 (2008)

Sabine, B., Fung Ang, S., y Schneider, G.A.On the mechanical properties of hierarchically structured biological materials. Biomaterials, 31, 6378-6385 (2010).

Samuel, S., Nag, S., Scharf, T. W. y Banerjee, R. Wear resistance of laser-deposited boride reinforced TiNb–Zr–Ta alloy composites for orthopedic implants, Materials Science and Engineering: C, 28, 414-420 (2008)

Shahryari, A., Omanovic, S. y Szpunar, J.A.Electrochemical formation of highly pitting resistant passive films on a biomedical grade 316LVM stainless steel surface, Materials Science and Engineering: C, 28, 94-106 (2008).

Tapash, R., Rautray, R. y Kyo-Han, K. Ion implantation of titanium based biomaterials, Progress in Materials Science, 56, 1137-1177 (2011).

Tjong, S.C., Electron microscope observations of phase decompositions in an austenitic Fe-8.7Al-29.7Mn1.04C alloy. Materials Characterization, 24,275–292 (1990).

Venugopalan, R. y Gaydon, J., A Review of Corrosion Behaviour of Surgical Implant Alloys, Perkin Elmer Instruments, 99-107, Princeton, USA (2001).

Woodman, J., Black, J. y Nunamaker, D., J. Biomed. Mater. Res: 17(1), 655-658 (1983).

Zion, B., The use of computer vision technologies in aquaculture – A review, Computers and Electronics in Agriculture, 88, 125-132 (2012)