Medición experimental de la densidad y viscosidad de líquidos utilizando visión artificial
87 páginas
- Autores:
-
Gaviria Alvarez, Julian Camilo
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2023
- Institución:
- Universidad EIA .
- Repositorio:
- Repositorio EIA .
- Idioma:
- spa
- OAI Identifier:
- oai:repository.eia.edu.co:11190/6067
- Acceso en línea:
- https://repository.eia.edu.co/handle/11190/6067
- Palabra clave:
- Visión artificial
Viscosidad cinemática
Densidad
Falling Ball
OpenCV
Machine vision
Kinematic viscosity
Density
- Rights
- openAccess
- License
- Derechos Reservados - Universidad EIA, 2023
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Medición experimental de la densidad y viscosidad de líquidos utilizando visión artificial |
| title |
Medición experimental de la densidad y viscosidad de líquidos utilizando visión artificial |
| spellingShingle |
Medición experimental de la densidad y viscosidad de líquidos utilizando visión artificial Visión artificial Viscosidad cinemática Densidad Falling Ball OpenCV Machine vision Kinematic viscosity Density |
| title_short |
Medición experimental de la densidad y viscosidad de líquidos utilizando visión artificial |
| title_full |
Medición experimental de la densidad y viscosidad de líquidos utilizando visión artificial |
| title_fullStr |
Medición experimental de la densidad y viscosidad de líquidos utilizando visión artificial |
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Medición experimental de la densidad y viscosidad de líquidos utilizando visión artificial |
| title_sort |
Medición experimental de la densidad y viscosidad de líquidos utilizando visión artificial |
| dc.creator.fl_str_mv |
Gaviria Alvarez, Julian Camilo |
| dc.contributor.advisor.none.fl_str_mv |
Méndez Mejía, Santiago |
| dc.contributor.author.none.fl_str_mv |
Gaviria Alvarez, Julian Camilo |
| dc.subject.proposal.spa.fl_str_mv |
Visión artificial Viscosidad cinemática Densidad |
| topic |
Visión artificial Viscosidad cinemática Densidad Falling Ball OpenCV Machine vision Kinematic viscosity Density |
| dc.subject.proposal.eng.fl_str_mv |
Falling Ball OpenCV Machine vision Kinematic viscosity Density |
| description |
87 páginas |
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2023 |
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2023-08-15T19:31:17Z |
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2023-08-15T19:31:17Z |
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2023 |
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spa |
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Derechos Reservados - Universidad EIA, 2023 |
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Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) |
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Universidad EIA |
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Otro |
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Escuela de Ingeniería y Ciencias Básicas |
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Envigado (Antioquia, Colombia) |
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Universidad EIA |
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Méndez Mejía, SantiagoGaviria Alvarez, Julian Camilo2023-08-15T19:31:17Z2023-08-15T19:31:17Z2023https://repository.eia.edu.co/handle/11190/606787 páginasRESUMEN: en el presente trabajo se propone y se desarrolla una técnica experimental para la medición de la densidad y viscosidad cinemática de líquidos utilizando técnicas de visión artificial tales como búsqueda de contornos, binarización y Optical Flow. La propuesta se fundamenta en el montaje de un viscometro de tipo Falling Ball a fin de corroborar si su implementación resulta tanto posible como favorable al prescindir de mediciones temporales realizadas por humanos. Con este fin, se utilizan los fundamentos físicos matemáticos concernientes al fenómeno de caída de cuerpos esféricos a través de un líquido para derivar las ecuaciones que describen tal fenómeno y que permiten el cálculo de las variables de interés. Para realizar las mediciones se utiliza la cámara de un celular Samsung A12, distintas probetas cilíndricas disponibles en la universidad EIA y por supuesto código desarrollado en Python a partir de la librería especializada en visión artificial, OpenCV, para el cálculo de las velocidades de las esferas. Se valida el método computacional propuesto para la medición de velocidades experimentales al reportar mediciones comparables a las que haría un ser humano, siendo que las diferencias sustanciales pueden atribuirse a la eliminación del factor humano (tiempos de reacción). Se reporta y analiza en profundidad la presencia de posibles factores de pared que se encargan de frenar las esferas y se observa como dichos factores se reducen sustancialmente al mejorar la relación entre los diámetros de la esfera y los tubos. Múltiples propuestas de estimación para las variables de interés son presentadas, dentro de las cuales se destacan el ajuste de parámetros asociados a la solución de la ecuación diferencial, estimación directa de las variables una vez que las esferas han alcanzado sus velocidades terminales y regresiones sobre los datos experimentales. Las dos primeras propuestas presentan resultados negativos, presumiblemente debido a los factores de pared que se encargan de hacer poco fiables los resultados obtenidos y que hicieron patente la necesidad de mejorar la razón entre los diámetros de esferas y tubos. Una vez implementada esta mejora práctica, la tercera de las propuestas de estimación resulto la más útil al permitir estimar las velocidades terminales de las esferas y a partir de estas obtener valores cercanos a los reportados en la literatura para las viscosidades objetivo. De esta manera, se confirma finalmente que el método aquí propuesto es válido y deseable en función de los objetivos propuestos, más que, sin embargo, por motivos prácticos no es posible desarrollarlo de manera apropiada, en vista de lo mismo, se presentan finalmente algunas reflexiones y consideraciones finales con respecto a los resultados del proyecto y que servirán tanto como camino ya recorrido como de sustento teórico-práctico para futuras investigaciones similares. en: This work proposes and develops an experimental technique for the measurement of the density and kinematic viscosity of liquids using artificial vision techniques such as contour search, binarization and Optical Flow. The proposal is based on the assembly of a Falling ball-type viscometer in order to corroborate if its implementation is both possible and favorable when dispensing with temporal measurements performed by humans. To this end, the physico-mathematical fundamentals concerning the phenomenon of the falling of spherical bodies through a liquid are used to derivate the equations that describe such phenomena and that allow the calculation of the variables of interest. To perform the measurements, we used the camera of a Samsung A12 cell phone and different cylindrical specimens available at the EIA university and, of course, code developed in Python from the library specialized in artificial vision, OpenCV, to calculate the velocities of the spheres. The proposed computational method for the measurement of experimental velocities is validated by reporting measurements comparable to those made by a human being, being that the substantial differences can be attributed to the elimination of the human factor (reaction times). The presence of possible wall factors responsible for slowing down the spheres are reported and analyzed in depth, and it is observed how these factors are substantially reduced by improving the ratio between the diameters of the sphere and the tube. Multiple estimation proposals for the variables of interest are presented, among which the adjustment of parameters associated with the solution of the differential equation, direct estimation of the variables once the spheres have reached their terminal velocities and regressions on the experimental data stand out. The first two proposals show negative results, presumably due to the wall factors that make the obtained results unreliable and that made evident the need to improve the ratio between the diameters of spheres and tubes. Once this practical improvement was implemented, the third of the estimation proposals turned out to be the most useful, since it allowed estimating the terminal velocities of the spheres and obtaining values close to those reported in the literature for the target viscosities. In this way, it is finally confirmed that the method proposed here is valid and desirable in terms of the proposed objectives, but that, however, for practical reasons, it is not possible to develop it in an appropriate way, in view of the same, some reflections and final considerations are finally presented with respect to the results of the project that will serve both as a road already traveled and as theoretical and practical support for future similar investigations.ABSTRACT: this work proposes and develops an experimental technique for the measurement of the density and kinematic viscosity of liquids using artificial vision techniques such as contour search, binarization and Optical Flow. The proposal is based on the assembly of a Falling ball-type viscometer in order to corroborate if its implementation is both possible and favorable when dispensing with temporal measurements performed by humans. To this end, the physico-mathematical fundamentals concerning the phenomenon of the falling of spherical bodies through a liquid are used to derivate the equations that describe such phenomena and that allow the calculation of the variables of interest. To perform the measurements, we used the camera of a Samsung A12 cell phone and different cylindrical specimens available at the EIA university and, of course, code developed in Python from the library specialized in artificial vision, OpenCV, to calculate the velocities of the spheres. The proposed computational method for the measurement of experimental velocities is validated by reporting measurements comparable to those made by a human being, being that the substantial differences can be attributed to the elimination of the human factor (reaction times). The presence of possible wall factors responsible for slowing down the spheres are reported and analyzed in depth, and it is observed how these factors are substantially reduced by improving the ratio between the diameters of the sphere and the tube. Multiple estimation proposals for the variables of interest are presented, among which the adjustment of parameters associated with the solution of the differential equation, direct estimation of the variables once the spheres have reached their terminal velocities and regressions on the experimental data stand out. The first two proposals show negative results, presumably due to the wall factors that make the obtained results unreliable and that made evident the need to improve the ratio between the diameters of spheres and tubes. Once this practical improvement was implemented, the third of the estimation proposals turned out to be the most useful, since it allowed estimating the terminal velocities of the spheres and obtaining values close to those reported in the literature for the target viscosities. In this way, it is finally confirmed that the method proposed here is valid and desirable in terms of the proposed objectives, but that, however, for practical reasons, it is not possible to develop it in an appropriate way, in view of the same, some reflections and final considerations are finally presented with respect to the results of the project that will serve both as a road already traveled and as theoretical and practical support for future similar investigations.PregradoOtroapplication/pdfspaUniversidad EIAOtroEscuela de Ingeniería y Ciencias BásicasEnvigado (Antioquia, Colombia)Derechos Reservados - Universidad EIA, 2023Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Medición experimental de la densidad y viscosidad de líquidos utilizando visión artificialTrabajo de grado - Pregradohttp://purl.org/coar/resource_type/c_7a1finfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/publishedVersionTexthttp://purl.org/redcol/resource_type/TPhttp://purl.org/coar/version/c_970fb48d4fbd8a85Visión artificialViscosidad cinemáticaDensidadFalling BallOpenCVMachine visionKinematic viscosityDensityLICENSElicense.txtlicense.txttext/plain; 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