Evaluación del campo de esfuerzos mediante el análisis, descripción y clasificación de la dinámica temporal de secuencias de imágenes de fotoelasticidad

La evaluación experimental del campo de esfuerzos es de importancia en múltiples áreas de la ingeniería porque describe la respuesta mecánica que exhibe una estructura al ser sometida a cargas de distinta naturaleza. En este campo de trabajo, los estudios de fotoelasticidad digital sobresalen entre...

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Autores:
Briñez de león, Juan Carlos
Tipo de recurso:
Work document
Fecha de publicación:
2020
Institución:
Universidad Nacional de Colombia
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Universidad Nacional de Colombia
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spa
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https://repositorio.unal.edu.co/handle/unal/78194
Palabra clave:
000 - Ciencias de la computación, información y obras generales::003 - Sistemas
Digital photoelasticity
Birefringence
Color fringe patterns
Stress field
Color fringe patterns
Digital image sequence processing
Pattern recognition
Computational hybrid methods.
Fotoelasticidad digital
Birrefringencia
Patrones de franjas de color
Campo de esfuerzos
Procesamiento digital de secuencias de imágenes
Reconocimiento de patrones
Métodos híbridos computacionales.
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id UNACIONAL2_67ad5235b62e124a52f662fbfa548b1a
oai_identifier_str oai:repositorio.unal.edu.co:unal/78194
network_acronym_str UNACIONAL2
network_name_str Universidad Nacional de Colombia
repository_id_str
dc.title.spa.fl_str_mv Evaluación del campo de esfuerzos mediante el análisis, descripción y clasificación de la dinámica temporal de secuencias de imágenes de fotoelasticidad
dc.title.alternative.spa.fl_str_mv Stress field evaluation by the analysis, description, and classification of temporal dynamics in photoelasticity image sequences
title Evaluación del campo de esfuerzos mediante el análisis, descripción y clasificación de la dinámica temporal de secuencias de imágenes de fotoelasticidad
spellingShingle Evaluación del campo de esfuerzos mediante el análisis, descripción y clasificación de la dinámica temporal de secuencias de imágenes de fotoelasticidad
000 - Ciencias de la computación, información y obras generales::003 - Sistemas
Digital photoelasticity
Birefringence
Color fringe patterns
Stress field
Color fringe patterns
Digital image sequence processing
Pattern recognition
Computational hybrid methods.
Fotoelasticidad digital
Birrefringencia
Patrones de franjas de color
Campo de esfuerzos
Procesamiento digital de secuencias de imágenes
Reconocimiento de patrones
Métodos híbridos computacionales.
title_short Evaluación del campo de esfuerzos mediante el análisis, descripción y clasificación de la dinámica temporal de secuencias de imágenes de fotoelasticidad
title_full Evaluación del campo de esfuerzos mediante el análisis, descripción y clasificación de la dinámica temporal de secuencias de imágenes de fotoelasticidad
title_fullStr Evaluación del campo de esfuerzos mediante el análisis, descripción y clasificación de la dinámica temporal de secuencias de imágenes de fotoelasticidad
title_full_unstemmed Evaluación del campo de esfuerzos mediante el análisis, descripción y clasificación de la dinámica temporal de secuencias de imágenes de fotoelasticidad
title_sort Evaluación del campo de esfuerzos mediante el análisis, descripción y clasificación de la dinámica temporal de secuencias de imágenes de fotoelasticidad
dc.creator.fl_str_mv Briñez de león, Juan Carlos
dc.contributor.advisor.spa.fl_str_mv Restrepo Martínez, Alejandro
Branch Bedoya, John William
dc.contributor.author.spa.fl_str_mv Briñez de león, Juan Carlos
dc.contributor.corporatename.spa.fl_str_mv Universidad Nacional de Colombia - Sede Medellín
dc.contributor.researchgroup.spa.fl_str_mv GIDIA: Grupo de Investigación y Desarrollo en Inteligencia Artificial
dc.subject.ddc.spa.fl_str_mv 000 - Ciencias de la computación, información y obras generales::003 - Sistemas
topic 000 - Ciencias de la computación, información y obras generales::003 - Sistemas
Digital photoelasticity
Birefringence
Color fringe patterns
Stress field
Color fringe patterns
Digital image sequence processing
Pattern recognition
Computational hybrid methods.
Fotoelasticidad digital
Birrefringencia
Patrones de franjas de color
Campo de esfuerzos
Procesamiento digital de secuencias de imágenes
Reconocimiento de patrones
Métodos híbridos computacionales.
dc.subject.proposal.eng.fl_str_mv Digital photoelasticity
Birefringence
Color fringe patterns
Stress field
Color fringe patterns
Digital image sequence processing
Pattern recognition
Computational hybrid methods.
dc.subject.proposal.spa.fl_str_mv Fotoelasticidad digital
Birrefringencia
Patrones de franjas de color
Campo de esfuerzos
Procesamiento digital de secuencias de imágenes
Reconocimiento de patrones
Métodos híbridos computacionales.
description La evaluación experimental del campo de esfuerzos es de importancia en múltiples áreas de la ingeniería porque describe la respuesta mecánica que exhibe una estructura al ser sometida a cargas de distinta naturaleza. En este campo de trabajo, los estudios de fotoelasticidad digital sobresalen entre otras técnicas por ser no invasivos, de campo completo, y altamente computacionales. No obstante, su implementación reporta limitaciones en términos de las múltiples configuraciones del polariscopio requeridas para adquirir las imágenes, cantidad de subprocesos computacionales, sesgo en zonas de concentración de esfuerzos, desempeños dependientes de la geometría de la estructura, e imposibilidad de identificar puntos isotrópicos y zonas de inconsistencias. Frente a las oportunidades de estudios en fotoelasticidad digital, esta investigación desarrolla un método basado en casos dinámicos donde la descripción y clasificación del comportamiento temporal del color son utilizados como estrategia clave para la evaluación del campo de esfuerzos en situaciones donde las técnicas convencionales reportan limitaciones. Dentro de los procesos realizados en este trabajo, inicialmente se presenta una conceptualización del campo de esfuerzos en estructuras cargadas, su relación con las propiedades ópticas birrefringentes, y los parámetros que intervienen en la formación de las imágenes con franjas de color. Con ello un repositorio híbrido de imágenes es generado. Posterior a la generación de las imágenes, una estrategia basada en la extracción, selección y clasificación de características es implementada teniendo en cuenta métodos convencionales, la longitud de arco y el conocimiento previo del comportamiento temporal del color dependiendo de las categorías de esfuerzos a la que se asocia. Los resultados demuestran que el método de clasificación de las dinámicas del color presenta mejor desempeño que los métodos convencionales seleccionados y sus derivaciones híbridas propuestas para su mejoramiento.
publishDate 2020
dc.date.accessioned.spa.fl_str_mv 2020-08-24T19:08:01Z
dc.date.available.spa.fl_str_mv 2020-08-24T19:08:01Z
dc.date.issued.spa.fl_str_mv 2020-07-30
dc.type.spa.fl_str_mv Documento de trabajo
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/workingPaper
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_8042
dc.type.content.spa.fl_str_mv Text
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/WP
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dc.identifier.uri.none.fl_str_mv https://repositorio.unal.edu.co/handle/unal/78194
url https://repositorio.unal.edu.co/handle/unal/78194
dc.language.iso.spa.fl_str_mv spa
language spa
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spelling Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de ColombiaAcceso abiertohttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Restrepo Martínez, Alejandrod8ce0ea8-f2b4-4096-ac42-028d1d34acc8-1Branch Bedoya, John William746e3553-266a-4721-8631-383ff8c51019-1Briñez de león, Juan Carlos64fda68f-2a8a-4ab0-a423-61074c10ec27Universidad Nacional de Colombia - Sede MedellínGIDIA: Grupo de Investigación y Desarrollo en Inteligencia Artificial2020-08-24T19:08:01Z2020-08-24T19:08:01Z2020-07-30https://repositorio.unal.edu.co/handle/unal/78194La evaluación experimental del campo de esfuerzos es de importancia en múltiples áreas de la ingeniería porque describe la respuesta mecánica que exhibe una estructura al ser sometida a cargas de distinta naturaleza. En este campo de trabajo, los estudios de fotoelasticidad digital sobresalen entre otras técnicas por ser no invasivos, de campo completo, y altamente computacionales. No obstante, su implementación reporta limitaciones en términos de las múltiples configuraciones del polariscopio requeridas para adquirir las imágenes, cantidad de subprocesos computacionales, sesgo en zonas de concentración de esfuerzos, desempeños dependientes de la geometría de la estructura, e imposibilidad de identificar puntos isotrópicos y zonas de inconsistencias. Frente a las oportunidades de estudios en fotoelasticidad digital, esta investigación desarrolla un método basado en casos dinámicos donde la descripción y clasificación del comportamiento temporal del color son utilizados como estrategia clave para la evaluación del campo de esfuerzos en situaciones donde las técnicas convencionales reportan limitaciones. Dentro de los procesos realizados en este trabajo, inicialmente se presenta una conceptualización del campo de esfuerzos en estructuras cargadas, su relación con las propiedades ópticas birrefringentes, y los parámetros que intervienen en la formación de las imágenes con franjas de color. Con ello un repositorio híbrido de imágenes es generado. Posterior a la generación de las imágenes, una estrategia basada en la extracción, selección y clasificación de características es implementada teniendo en cuenta métodos convencionales, la longitud de arco y el conocimiento previo del comportamiento temporal del color dependiendo de las categorías de esfuerzos a la que se asocia. Los resultados demuestran que el método de clasificación de las dinámicas del color presenta mejor desempeño que los métodos convencionales seleccionados y sus derivaciones híbridas propuestas para su mejoramiento.Evaluating the stress field is an important task in multiple engineering areas because it describes the mechanical response that a structure resist under load application. In this study field, digital photoelasticity stand out among other techniques for being non-invasive, full-field, and highly computational. However, its application reports drawbacks in terms of the multiple polariscope configurations it requires to acquire the images, number of computational procedures, lost information in stress concentration zones, performance that dependent on the structure geometry, and the impossibility of identifying isotropic points and inconsistency zones. Taking advantages of the research opportunities in digital photoelasticity, this work develops a method for evaluating the stress information in dynamic cases. Here, describing and classifying the temporal behavior of color in photoelasticity image sequences are used as a key strategy for the evaluation of the stress field in situations where conventional techniques report limitations. Into the processes carried out in this work, a conceptualization of the stress field in loaded structures, its relationship with birefringent optical properties, and the parameters involved in the formation of images with color fringes are initially presented. With this a hybrid image repository is generated. After the generation of the images, a strategy based on the extraction, selection and classification of characteristics is implemented considering conventional methods, the arc length and the prior knowledge of the temporal behavior of the color depending on the stress categories to which they are associated to. The results demonstrate that the new method of classifying color dynamics presents better performance than the selected conventional methods and their hybrid derivations proposed to improve them.Doctorado273application/pdfspa000 - Ciencias de la computación, información y obras generales::003 - SistemasDigital photoelasticityBirefringenceColor fringe patternsStress fieldColor fringe patternsDigital image sequence processingPattern recognitionComputational hybrid methods.Fotoelasticidad digitalBirrefringenciaPatrones de franjas de colorCampo de esfuerzosProcesamiento digital de secuencias de imágenesReconocimiento de patronesMétodos híbridos computacionales.Evaluación del campo de esfuerzos mediante el análisis, descripción y clasificación de la dinámica temporal de secuencias de imágenes de fotoelasticidadStress field evaluation by the analysis, description, and classification of temporal dynamics in photoelasticity image sequencesDocumento de trabajoinfo:eu-repo/semantics/workingPaperinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_8042Texthttp://purl.org/redcol/resource_type/WPMedellín - Minas - Doctorado en Ingeniería - SistemasUniversidad Nacional de Colombia - Sede MedellínBriñez-de León, J. C., Restrepo-Martínez, A., & Branch-Bedoya, J. W. (2019). Computational analysis of Bayer colour filter arrays and demosaicking algorithms in digital photoelasticity. Optics and Lasers in Engineering, 122, 195-208.Toro, H. F., Briñez-de León, J. C., Martinez, A. R., & Bedoya, J. W. B. (2018). Fringe patterns recognition in digital photoelasticity images using texture features and multispectral wavelength analysis. Optical Engineering, 57(9), 093105.Briñez-de León, J. C., Alejandro Restrepo Martínez, John W. Branch, (2018). Computational hybrid phase shifting technique applied to digital photoelasticity, In Optik - International Journal for Light and Electron Optics, Volume 157, Pages 287-297, ISSN 0030-4026Pérez, U., Camilo, J., Motta, G. C., Briñez-de León, J. C., & Restrepo-Martínez, A. (2017). Validación del uso de fotoelasticidad como herramienta para los cursos de Mecánica de Sólidos. Revista EIA, 14(28), 117-131Briñez-de León, J. C.; Fandiño Toro, Hermes A; Restrepo Martínez, Alejandro; Branch Bedoya, John W., (2017). Análisis de resolución en imágenes de fotoelasticidad: caso carga dinámica. Visión Electrónica. Vol 1. No. 1, Universidad Distrital Francisco José CaldasFandiño Toro, Hermes A; Briñez-de León, J. C.; Restrepo Martínez, Alejandro; Branch Bedoya, John W., (2017). Análisis de campos de esfuerzos utilizando fotoelasticidad visible e infrarroja. Visión Electrónica. Vol 1. No. 1, Universidad Distrital Francisco José CaldasBriñez-de León, J. C., Alejandro Restrepo, John W. Branch y Carlos Madrigal. Desenvolvimiento de fase RGB aplicado a secuencias de imágenes de fotoelasticidad capturadas de la tracción de películas plásticas. XIV Encuentro Nacional De Óptica V Conferencia Andina y del Caribe En Óptica y sus Aplicaciones ENO - CANCOA 2015. Cali - Colombia. 16-20 de Noviembre de 2015Briñez-de León, J. C., Alejandro Restrepo, John W. Branch. Evaluación Temporal de los Ordenes de Franjas de Color Utilizando Análisis de Saturación en Secuencias de Imágenes de Fotoelasticidad. Décimo segundo Congreso Iberoamericano de Ingeniería Mecánica (CIBIM XII- 2015), Guayaquil-Ecuador. Noviembre 10-13 de 2015Fernando Melendez, Briñez-de León, J. C., Alejandro Restrepo, John W. Branch. Identificación de variaciones del efecto de la temperatura en la deformación de películas plásticas analizando el comportamiento temporal de la fotoelasticidad. XIV Encuentro Nacional De Óptica V Conferencia Andina y del Caribe En Óptica y sus Aplicaciones ENO - CANCOA 2015. Cali- Colombia. 16-20 de Noviembre de 2015Briñez-de León, J. C., A. R. Martínez and J. W. B. Bedoya, "High stress concentration analysis using RGB intensity changes in dynamic photoelasticity videos," 2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA), Bucaramanga, 2016, pp. 1-7.doi: 10.1109/STSIVA.2016.7743324Briñez-de León, J. C., Alejandro Restrepo M.; John W. Branch; Time-space analysis in photoelasticity images using recurrent neural networks to detect zones with stress concentration. Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 99712P (September 28, 2016); doi:10.1117/12.2237373Briñez-de León, J. C., Hermes Alexander Fandiño-Toro, Alejandro Restrepo-Martínez, John W. Branch. Evaluación de la pérdida de resolución en imágenes de fotoelasticidad debido al incremento de la carga. VIII Congreso Internacional de Ingeniería Mecánica y Mecatrónica y IV de Materiales, Energía y Medioambiente, Medellín, Colombia. 2017/4/26Briñez-de León, J. C., D. A. Patiño Cortes, A. Restrepo Martínez, and J. W. Branch Bedoya, "Computational Detection of Salient Information to Identify High Stress and Ambiguity Regions in Digital Photoelasticity Images," in Imaging and Applied Optics 2017 (3D, AIO, COSI, IS, MATH, pcAOP), OSA Technical Digest (online) (Optical Society of America, 2017), paper IM4E.2Briñez-de León, J. C., Alejandro Restrepo M., John W. Branch, "Computational reduction of the image sets required in conventional phase shifting methods applied to digital photoelasticity" Proc. SPIE 10395, Optics and Photonics for Information Processing XI, 103950K (24 August 2017); doi: 10.1117/12.2273431Hermes Fandiño Toro, Briñez-de León, J. C., Alejandro Restrepo Martínez, John W. Branch Bedoya, "Texture analysis integrated to infrared light sources for identifying high fringe concentrations in digital photoelasticity," Proc. SPIE 10396, Applications of Digital Image Processing XL, 103962D (19 September 2017); doi: 10.1117/12.2273258Juan Camilo Urango Pérez, Guillermo Carmen Motta, Briñez-de León, J. C., Alejandro Restrepo Martinez. Validation of the photoelasticity method as a tool for the enhancement of learning and design processes in solid mechanics. Congreso Internacional de Formación y Modelación en Ciencias Básicas. Universidad de Medellín. 2017. Página 217. ISBN-ebook: 978-958-8992-46-7Briñez-de León, J. C., H. A. Fandiño Toro, A. Restrepo M, and J. W. Branch, "Bayer and demosaicking effect for imaging the stress field in digital photoelasticity," in Imaging and Applied Optics 2018 (3D, AO, AIO, COSI, DH, IS, LACSEA, LS&C, MATH, pcAOP), OSA Technical Digest (Optical Society of America, 2018), paper IW2B.3.Briñez-de León, J. C., Fandiño, H. A., Restrepo, A., & Branch, J. W. (2018, September). Computational analysis of stress map variations by industrial light sources and load additions in digital photoelasticity. In Optics and Photonics for Information Processing XII (Vol. 10751, p. 107510G). International Society for Optics and PhotonicsH. F. Toro, Briñez-de León, J. C., A. Restrepo Martínez, and J. W. Branch Bedoya, "Relevance analysis for texture descriptors in studies of dynamic photoelasticity," in Imaging and Applied Optics 2018 (3D, AO, AIO, COSI, DH, IS, LACSEA, LS&C, MATH, pcAOP), OSA Technical Digest (Optical Society of America, 2018), paper JM4A.37Briñez-de León, J. C., Martínez, A. R., & Bedoya, J. W. B. (2019, June). Fast Fourier Transform as Color Variation Descriptor for Imaging the Stress Field from Photoelasticity Videos. In Imaging Systems and Applications (pp. JW2A-46). Optical Society of AmericaToro, H. F., Briñez-de León, J. C., RestrepoMartínez, A., & Branch, J. W. (2019, June). Texture analysis for evaluating the Bayer and demosaicking effects in photoelasticity images. In Computational Optical Sensing and Imaging (pp. JW2A-50). Optical Society of AmericaRestrepo-Martinez, A., & Briñez-de León, J. C., (2019, September). Dynamic color descriptor based Frenet-Serret to classify stress zones from pixel variations recorded in photoelasticity videos. In Optics and Photonics for Information Processing XIII (Vol. 11136, p. 111360G). International Society for Optics and PhotonicsBriñez-de León, J. C., Mery, D., Restrepo, A., & Branch, J. W. (2019, September). One-dimensional local binary pattern based color descriptor to classify stress values from photoelasticity videos. In Optics and Photonics for Information Processing XIII (Vol. 11136, p. 1113607). International Society for Optics and Photonics.H. J. Jiménez, “Comportamiento mecánico y microestructural de la aleación AlMgSi para conductores eléctricos,” Rev. UIS Ing., vol. 18, no. 2, pp. 199–211, 2019.S. 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Optical Engineering 54.8 (2015): 081209.ORIGINAL88032810.2020.pdf88032810.2020.pdfTesis de Doctorado en Ingeniería - Sistemasapplication/pdf12086764https://repositorio.unal.edu.co/bitstream/unal/78194/4/88032810.2020.pdf1b3f4adb65f5ce21bccb305f3c1577d1MD54LICENSElicense.txtlicense.txttext/plain; charset=utf-83895https://repositorio.unal.edu.co/bitstream/unal/78194/5/license.txte2f63a891b6ceb28c3078128251851bfMD55CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8701https://repositorio.unal.edu.co/bitstream/unal/78194/6/license_rdf42fd4ad1e89814f5e4a476b409eb708cMD56THUMBNAIL88032810.2020.pdf.jpg88032810.2020.pdf.jpgGenerated Thumbnailimage/jpeg5796https://repositorio.unal.edu.co/bitstream/unal/78194/7/88032810.2020.pdf.jpgf7549fbefb7f0fae74d84a2537f42ed8MD57unal/78194oai:repositorio.unal.edu.co:unal/781942024-07-06 23:51:13.647Repositorio Institucional Universidad Nacional de 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GVyZWNob3MgZGUgYXV0b3IgcXVlIGNvbmxsZXZlIGxhIGRpc3RyaWJ1Y2nDs24gZGUgZXN0b3MgYXJjaGl2b3MgeSBtZXRhZGF0b3MuCkFsIGhhY2VyIGNsaWMgZW4gZWwgc2lndWllbnRlIGJvdMOzbiwgdXN0ZWQgaW5kaWNhIHF1ZSBlc3TDoSBkZSBhY3VlcmRvIGNvbiBlc3RvcyB0w6lybWlub3MuCg==

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