Preprocesador de fuzzy inference system (FIS) y motor de inferencia difusa para la plataforma de desarrollo embebida freescale twr-k70f120m
Este documento detalla el desarrollo de una solución software que satisface la necesidad presente en el proyecto de investigación 8556 “Desarrollo de un prototipo de pozo inteligente para CEC” de Campo Escuela Colorado, el cual busca reducir costos de operación y gastos de capital, aumentar los nive...
- Autores:
-
Zarate Vasquez, Cristhian Alonso
- Tipo de recurso:
- http://purl.org/coar/version/c_b1a7d7d4d402bcce
- Fecha de publicación:
- 2016
- Institución:
- Universidad Industrial de Santander
- Repositorio:
- Repositorio UIS
- Idioma:
- spa
- OAI Identifier:
- oai:noesis.uis.edu.co:20.500.14071/34234
- Palabra clave:
- Lógica Difusa
Modelos Difusos
Fuzzy Inference System
Motores De Inferencia Difusa
Sistemas Embebidos.
This document details the development of a software solution that satisfies the needs present in the research project 8556 “Desarrollo de un prototipo de pozo inteligente para Campo Escuela Colorado” (Development of a Smart Well prototype for Campo Escuela Colorado)
which seeks to reduce operational costs and capital expense
increase production and reserve levels
and to accurately detect failures that may occur in an oil well
by using software and hardware elements in mechanical pump type artificial lift systems (Smart Well and Smart Field concepts). The research project 8556 in its first two stages
developed the “Controlador de Pozo Inteligente” (Smart Well Controller)
abbreviated CPI
a hardware and software solution that collects and presents information about operation of a mechanical pump system through sensors that transmit wirelessly to an embedded system located in the vicinity of the machinery. The bachelor thesis “Fuzzy Inference System (FIS) Preprocessor and Fuzzy Inference Engine for the Freescale TWR-K70F120M Embedded Platform” proposed and implemented the software application “Fuzzy Inference System Preprocessor for Embedded Systems”
FISPES
which is able transform a fuzzy model
contained in a plain text file
into a fuzzy inference engine that can be run on the embedded system located in the CPI.
- Rights
- License
- Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
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dc.title.none.fl_str_mv |
Preprocesador de fuzzy inference system (FIS) y motor de inferencia difusa para la plataforma de desarrollo embebida freescale twr-k70f120m |
dc.title.english.none.fl_str_mv |
Fuzzy Logic, Fuzzy Models, Fuzzy Inference System, Fuzzy Inference Engine, Embedded Systems. |
title |
Preprocesador de fuzzy inference system (FIS) y motor de inferencia difusa para la plataforma de desarrollo embebida freescale twr-k70f120m |
spellingShingle |
Preprocesador de fuzzy inference system (FIS) y motor de inferencia difusa para la plataforma de desarrollo embebida freescale twr-k70f120m Lógica Difusa Modelos Difusos Fuzzy Inference System Motores De Inferencia Difusa Sistemas Embebidos. This document details the development of a software solution that satisfies the needs present in the research project 8556 “Desarrollo de un prototipo de pozo inteligente para Campo Escuela Colorado” (Development of a Smart Well prototype for Campo Escuela Colorado) which seeks to reduce operational costs and capital expense increase production and reserve levels and to accurately detect failures that may occur in an oil well by using software and hardware elements in mechanical pump type artificial lift systems (Smart Well and Smart Field concepts). The research project 8556 in its first two stages developed the “Controlador de Pozo Inteligente” (Smart Well Controller) abbreviated CPI a hardware and software solution that collects and presents information about operation of a mechanical pump system through sensors that transmit wirelessly to an embedded system located in the vicinity of the machinery. The bachelor thesis “Fuzzy Inference System (FIS) Preprocessor and Fuzzy Inference Engine for the Freescale TWR-K70F120M Embedded Platform” proposed and implemented the software application “Fuzzy Inference System Preprocessor for Embedded Systems” FISPES which is able transform a fuzzy model contained in a plain text file into a fuzzy inference engine that can be run on the embedded system located in the CPI. |
title_short |
Preprocesador de fuzzy inference system (FIS) y motor de inferencia difusa para la plataforma de desarrollo embebida freescale twr-k70f120m |
title_full |
Preprocesador de fuzzy inference system (FIS) y motor de inferencia difusa para la plataforma de desarrollo embebida freescale twr-k70f120m |
title_fullStr |
Preprocesador de fuzzy inference system (FIS) y motor de inferencia difusa para la plataforma de desarrollo embebida freescale twr-k70f120m |
title_full_unstemmed |
Preprocesador de fuzzy inference system (FIS) y motor de inferencia difusa para la plataforma de desarrollo embebida freescale twr-k70f120m |
title_sort |
Preprocesador de fuzzy inference system (FIS) y motor de inferencia difusa para la plataforma de desarrollo embebida freescale twr-k70f120m |
dc.creator.fl_str_mv |
Zarate Vasquez, Cristhian Alonso |
dc.contributor.advisor.none.fl_str_mv |
Gomez Florez, Luis Carlos Meneses Florez, Jorge Enrique |
dc.contributor.author.none.fl_str_mv |
Zarate Vasquez, Cristhian Alonso |
dc.subject.none.fl_str_mv |
Lógica Difusa Modelos Difusos Fuzzy Inference System Motores De Inferencia Difusa Sistemas Embebidos. |
topic |
Lógica Difusa Modelos Difusos Fuzzy Inference System Motores De Inferencia Difusa Sistemas Embebidos. This document details the development of a software solution that satisfies the needs present in the research project 8556 “Desarrollo de un prototipo de pozo inteligente para Campo Escuela Colorado” (Development of a Smart Well prototype for Campo Escuela Colorado) which seeks to reduce operational costs and capital expense increase production and reserve levels and to accurately detect failures that may occur in an oil well by using software and hardware elements in mechanical pump type artificial lift systems (Smart Well and Smart Field concepts). The research project 8556 in its first two stages developed the “Controlador de Pozo Inteligente” (Smart Well Controller) abbreviated CPI a hardware and software solution that collects and presents information about operation of a mechanical pump system through sensors that transmit wirelessly to an embedded system located in the vicinity of the machinery. The bachelor thesis “Fuzzy Inference System (FIS) Preprocessor and Fuzzy Inference Engine for the Freescale TWR-K70F120M Embedded Platform” proposed and implemented the software application “Fuzzy Inference System Preprocessor for Embedded Systems” FISPES which is able transform a fuzzy model contained in a plain text file into a fuzzy inference engine that can be run on the embedded system located in the CPI. |
dc.subject.keyword.none.fl_str_mv |
This document details the development of a software solution that satisfies the needs present in the research project 8556 “Desarrollo de un prototipo de pozo inteligente para Campo Escuela Colorado” (Development of a Smart Well prototype for Campo Escuela Colorado) which seeks to reduce operational costs and capital expense increase production and reserve levels and to accurately detect failures that may occur in an oil well by using software and hardware elements in mechanical pump type artificial lift systems (Smart Well and Smart Field concepts). The research project 8556 in its first two stages developed the “Controlador de Pozo Inteligente” (Smart Well Controller) abbreviated CPI a hardware and software solution that collects and presents information about operation of a mechanical pump system through sensors that transmit wirelessly to an embedded system located in the vicinity of the machinery. The bachelor thesis “Fuzzy Inference System (FIS) Preprocessor and Fuzzy Inference Engine for the Freescale TWR-K70F120M Embedded Platform” proposed and implemented the software application “Fuzzy Inference System Preprocessor for Embedded Systems” FISPES which is able transform a fuzzy model contained in a plain text file into a fuzzy inference engine that can be run on the embedded system located in the CPI. |
description |
Este documento detalla el desarrollo de una solución software que satisface la necesidad presente en el proyecto de investigación 8556 “Desarrollo de un prototipo de pozo inteligente para CEC” de Campo Escuela Colorado, el cual busca reducir costos de operación y gastos de capital, aumentar los niveles de producción y reservas y detectar de manera precisa y oportuna las fallas que se puedan presentar en un pozo, mediante el uso de elementos hardware y software en los sistemas de levantamiento artificial de tipo bombeo mecánico (concepto de Pozo y Campo Inteligentes). El proyecto de investigación 8556 desarrolló en sus dos primeras fases el “Controlador de Pozo Inteligente” CPI, solución de hardware y software que permite recolectar y presentar la información de operación de un sistema de bombeo mecánico a través de sensores que se conectan de manera inalámbrica a un dispositivo embebido ubicado en la cercanía de la cabeza de pozo. El proyecto denominado “Preprocesador de Fuzzy Inference System (FIS) y Motor de Inferencia Difusa para la Plataforma de Desarrollo Embebida Freescale TWRK70F120M” propuso e implementó la aplicación software “Preprocesador de Fuzzy Inference System para Plataformas Embebidas” FISPES, la cual es capaz de transformar un modelo difuso, contenido en un archivo de texto, en un motor de inferencia que se ejecuta sobre el dispositivo embebido presente en el CPI. |
publishDate |
2016 |
dc.date.available.none.fl_str_mv |
2016 2024-03-03T22:35:50Z |
dc.date.created.none.fl_str_mv |
2016 |
dc.date.issued.none.fl_str_mv |
2016 |
dc.date.accessioned.none.fl_str_mv |
2024-03-03T22:35:50Z |
dc.type.local.none.fl_str_mv |
Tesis/Trabajo de grado - Monografía - Pregrado |
dc.type.hasversion.none.fl_str_mv |
http://purl.org/coar/resource_type/c_7a1f |
dc.type.coar.none.fl_str_mv |
http://purl.org/coar/version/c_b1a7d7d4d402bcce |
format |
http://purl.org/coar/version/c_b1a7d7d4d402bcce |
dc.identifier.uri.none.fl_str_mv |
https://noesis.uis.edu.co/handle/20.500.14071/34234 |
dc.identifier.instname.none.fl_str_mv |
Universidad Industrial de Santander |
dc.identifier.reponame.none.fl_str_mv |
Universidad Industrial de Santander |
dc.identifier.repourl.none.fl_str_mv |
https://noesis.uis.edu.co |
url |
https://noesis.uis.edu.co/handle/20.500.14071/34234 https://noesis.uis.edu.co |
identifier_str_mv |
Universidad Industrial de Santander |
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spa |
language |
spa |
dc.rights.none.fl_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
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http://purl.org/coar/access_right/c_abf2 |
dc.rights.license.none.fl_str_mv |
Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) |
dc.rights.uri.none.fl_str_mv |
http://creativecommons.org/licenses/by-nc/4.0 |
dc.rights.creativecommons.none.fl_str_mv |
Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) |
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Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by-nc/4.0 Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) http://purl.org/coar/access_right/c_abf2 |
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application/pdf |
dc.publisher.none.fl_str_mv |
Universidad Industrial de Santander |
dc.publisher.faculty.none.fl_str_mv |
Facultad de Ingenierías Fisicomecánicas |
dc.publisher.program.none.fl_str_mv |
Ingeniería de Sistemas |
dc.publisher.school.none.fl_str_mv |
Escuela de Ingeniería de Sistemas e Informática |
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Universidad Industrial de Santander |
institution |
Universidad Industrial de Santander |
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Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)http://creativecommons.org/licenses/by/4.0/http://creativecommons.org/licenses/by-nc/4.0Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)http://purl.org/coar/access_right/c_abf2Gomez Florez, Luis CarlosMeneses Florez, Jorge EnriqueZarate Vasquez, Cristhian Alonso2024-03-03T22:35:50Z20162024-03-03T22:35:50Z20162016https://noesis.uis.edu.co/handle/20.500.14071/34234Universidad Industrial de SantanderUniversidad Industrial de Santanderhttps://noesis.uis.edu.coEste documento detalla el desarrollo de una solución software que satisface la necesidad presente en el proyecto de investigación 8556 “Desarrollo de un prototipo de pozo inteligente para CEC” de Campo Escuela Colorado, el cual busca reducir costos de operación y gastos de capital, aumentar los niveles de producción y reservas y detectar de manera precisa y oportuna las fallas que se puedan presentar en un pozo, mediante el uso de elementos hardware y software en los sistemas de levantamiento artificial de tipo bombeo mecánico (concepto de Pozo y Campo Inteligentes). El proyecto de investigación 8556 desarrolló en sus dos primeras fases el “Controlador de Pozo Inteligente” CPI, solución de hardware y software que permite recolectar y presentar la información de operación de un sistema de bombeo mecánico a través de sensores que se conectan de manera inalámbrica a un dispositivo embebido ubicado en la cercanía de la cabeza de pozo. El proyecto denominado “Preprocesador de Fuzzy Inference System (FIS) y Motor de Inferencia Difusa para la Plataforma de Desarrollo Embebida Freescale TWRK70F120M” propuso e implementó la aplicación software “Preprocesador de Fuzzy Inference System para Plataformas Embebidas” FISPES, la cual es capaz de transformar un modelo difuso, contenido en un archivo de texto, en un motor de inferencia que se ejecuta sobre el dispositivo embebido presente en el CPI.PregradoIngeniero de SistemasFuzzy inference system (fis) preprocessor and fuzzy inference engine for the freescale twr-k70f120m embedded platformapplication/pdfspaUniversidad Industrial de SantanderFacultad de Ingenierías FisicomecánicasIngeniería de SistemasEscuela de Ingeniería de Sistemas e InformáticaLógica DifusaModelos DifusosFuzzy Inference SystemMotores De Inferencia DifusaSistemas Embebidos.This document details the development of a software solution that satisfies the needs present in the research project 8556 “Desarrollo de un prototipo de pozo inteligente para Campo Escuela Colorado” (Development of a Smart Well prototype for Campo Escuela Colorado)which seeks to reduce operational costs and capital expenseincrease production and reserve levelsand to accurately detect failures that may occur in an oil wellby using software and hardware elements in mechanical pump type artificial lift systems (Smart Well and Smart Field concepts). The research project 8556 in its first two stagesdeveloped the “Controlador de Pozo Inteligente” (Smart Well Controller)abbreviated CPIa hardware and software solution that collects and presents information about operation of a mechanical pump system through sensors that transmit wirelessly to an embedded system located in the vicinity of the machinery. The bachelor thesis “Fuzzy Inference System (FIS) Preprocessor and Fuzzy Inference Engine for the Freescale TWR-K70F120M Embedded Platform” proposed and implemented the software application “Fuzzy Inference System Preprocessor for Embedded Systems”FISPESwhich is able transform a fuzzy modelcontained in a plain text fileinto a fuzzy inference engine that can be run on the embedded system located in the CPI.Preprocesador de fuzzy inference system (FIS) y motor de inferencia difusa para la plataforma de desarrollo embebida freescale twr-k70f120mFuzzy Logic, Fuzzy Models, Fuzzy Inference System, Fuzzy Inference Engine, Embedded Systems.Tesis/Trabajo de grado - Monografía - Pregradohttp://purl.org/coar/resource_type/c_7a1fhttp://purl.org/coar/version/c_b1a7d7d4d402bcceORIGINALCarta de autorización.pdfapplication/pdf4847419https://noesis.uis.edu.co/bitstreams/43efc8d1-73b6-4928-89fa-1e4b4378f944/download2cba18a7182e7c879f72175f9c5849b8MD51Documento.pdfapplication/pdf5509286https://noesis.uis.edu.co/bitstreams/2a1c72b0-d2bb-41b0-9ef5-170db4327f93/downloade542908a3426976d1587cda3efee6227MD52Nota de proyecto.pdfapplication/pdf4847419https://noesis.uis.edu.co/bitstreams/eca03179-2232-4289-b761-c976a1b41a9f/download2fc0aa7592fa8ba56bfaf28d9b4d9b3fMD5320.500.14071/34234oai:noesis.uis.edu.co:20.500.14071/342342024-03-03 17:35:50.324http://creativecommons.org/licenses/by-nc/4.0http://creativecommons.org/licenses/by/4.0/open.accesshttps://noesis.uis.edu.coDSpace at UISnoesis@uis.edu.co |