Desarrollo de un sistema embebido con tecnología DSP para un sistema multisensorial (Nariz electrónica)
This article consists in the development of an embedded system with DSP technology to be applied to a multi-sensory system (i.e. Electronic Nose). The idea of the present study was to improve the efficiency of these multisensory systems in portable applications, using different algorithms to classif...
- Autores:
-
Durán-Acevedo, Cristhian Manuel
Torres-López, Isaac
- Tipo de recurso:
- Fecha de publicación:
- 2014
- Institución:
- Universidad Santo Tomás
- Repositorio:
- Universidad Santo Tomás
- Idioma:
- spa
- OAI Identifier:
- oai:repository.usta.edu.co:11634/36104
- Acceso en línea:
- http://revistas.ustabuca.edu.co/index.php/ITECKNE/article/view/515
- Palabra clave:
- Rights
- License
- Copyright (c) 2018 ITECKNE
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Durán-Acevedo, Cristhian ManuelTorres-López, Isaac2014-09-17http://revistas.ustabuca.edu.co/index.php/ITECKNE/article/view/51510.15332/iteckne.v11i1.515This article consists in the development of an embedded system with DSP technology to be applied to a multi-sensory system (i.e. Electronic Nose). The idea of the present study was to improve the efficiency of these multisensory systems in portable applications, using different algorithms to classify three-class of volatile compounds, detected by a chemical gas sensor array. The Code Composer Studio (CCS) software was coupled with Matlab for programming the DSP TMS320F28335 card of Texas Instruments. The results were obtained from samples of wine of three different denominations (i.e., apple, red and Locker), which were then classified by processing algorithms (i.e. artificial neural networks). The system was validated by the technique of principal component analysis (PCA), to verify repeatability and selectivity of the measurement system. In the results, 83.4% of success rate in classification of the measures was obtained using DSP Hardware, through the implementation of an Artificial Neuronal Network (ANN).Este artículo consiste en el desarrollo de un sistema integrado con tecnología DSP para ser aplicado a un sistema multi-sensorial (es decir, nariz electrónica). La idea de este estudio fue mejorar la eficiencia de estos sistemas multisensoriales en aplicaciones portátiles, usando diferentes algoritmos para clasificar tres clases de compuestos volátiles detectados por una matriz de sensores de gases químicos. El software CodeComposer Studio (CCS) fue acoplado con Matlab para la programación de la tarjeta DSP TMS320F28335 de Texas Instruments. Los resultados se obtuvieron a partir de muestras de vino de tres denominaciones diferentes (es decir, manzana, rojo y casillero), que luego fueron clasificadas mediante algoritmos de procesamiento (redes neuronales artificiales). El sistema fue validado mediante la técnica de análisis de componentes principales (ACP), para verificar la reproducibilidad y selectividad del sistema de medición. En los resultados se logró un 83,4 % de tasa de éxito en la calificación de las medidas utilizando DSP Hardware,a través de la implementación de una Red NeuronalArtificial (RNA).application/pdfspaUniversidad Santo Tomás. Seccional Bucaramangahttp://revistas.ustabuca.edu.co/index.php/ITECKNE/article/view/515/407ITECKNE; Vol 11 No 1 (2014); 27-40ITECKNE; Vol 11 No 1 (2014); 27-402339-34831692-1798Copyright (c) 2018 ITECKNEhttp://purl.org/coar/access_right/c_abf2Desarrollo de un sistema embebido con tecnología DSP para un sistema multisensorial (Nariz electrónica)Development of embedded system with DSP technology for multisensor system (Electronic nose)info:eu-repo/semantics/articlehttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb111634/36104oai:repository.usta.edu.co:11634/361042023-07-14 16:20:32.49metadata only accessRepositorio Universidad Santo Tomásnoreply@usta.edu.co |
| dc.title.spa.fl_str_mv |
Desarrollo de un sistema embebido con tecnología DSP para un sistema multisensorial (Nariz electrónica) |
| dc.title.alternative.eng.fl_str_mv |
Development of embedded system with DSP technology for multisensor system (Electronic nose) |
| title |
Desarrollo de un sistema embebido con tecnología DSP para un sistema multisensorial (Nariz electrónica) |
| spellingShingle |
Desarrollo de un sistema embebido con tecnología DSP para un sistema multisensorial (Nariz electrónica) |
| title_short |
Desarrollo de un sistema embebido con tecnología DSP para un sistema multisensorial (Nariz electrónica) |
| title_full |
Desarrollo de un sistema embebido con tecnología DSP para un sistema multisensorial (Nariz electrónica) |
| title_fullStr |
Desarrollo de un sistema embebido con tecnología DSP para un sistema multisensorial (Nariz electrónica) |
| title_full_unstemmed |
Desarrollo de un sistema embebido con tecnología DSP para un sistema multisensorial (Nariz electrónica) |
| title_sort |
Desarrollo de un sistema embebido con tecnología DSP para un sistema multisensorial (Nariz electrónica) |
| dc.creator.fl_str_mv |
Durán-Acevedo, Cristhian Manuel Torres-López, Isaac |
| dc.contributor.author.none.fl_str_mv |
Durán-Acevedo, Cristhian Manuel Torres-López, Isaac |
| description |
This article consists in the development of an embedded system with DSP technology to be applied to a multi-sensory system (i.e. Electronic Nose). The idea of the present study was to improve the efficiency of these multisensory systems in portable applications, using different algorithms to classify three-class of volatile compounds, detected by a chemical gas sensor array. The Code Composer Studio (CCS) software was coupled with Matlab for programming the DSP TMS320F28335 card of Texas Instruments. The results were obtained from samples of wine of three different denominations (i.e., apple, red and Locker), which were then classified by processing algorithms (i.e. artificial neural networks). The system was validated by the technique of principal component analysis (PCA), to verify repeatability and selectivity of the measurement system. In the results, 83.4% of success rate in classification of the measures was obtained using DSP Hardware, through the implementation of an Artificial Neuronal Network (ANN). |
| publishDate |
2014 |
| dc.date.issued.none.fl_str_mv |
2014-09-17 |
| dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
| dc.type.drive.none.fl_str_mv |
info:eu-repo/semantics/article |
| dc.identifier.none.fl_str_mv |
http://revistas.ustabuca.edu.co/index.php/ITECKNE/article/view/515 10.15332/iteckne.v11i1.515 |
| url |
http://revistas.ustabuca.edu.co/index.php/ITECKNE/article/view/515 |
| identifier_str_mv |
10.15332/iteckne.v11i1.515 |
| dc.language.iso.none.fl_str_mv |
spa |
| language |
spa |
| dc.relation.none.fl_str_mv |
http://revistas.ustabuca.edu.co/index.php/ITECKNE/article/view/515/407 |
| dc.relation.citationissue.spa.fl_str_mv |
ITECKNE; Vol 11 No 1 (2014); 27-40 |
| dc.relation.citationissue.eng.fl_str_mv |
ITECKNE; Vol 11 No 1 (2014); 27-40 |
| dc.relation.citationissue.none.fl_str_mv |
2339-3483 1692-1798 |
| dc.rights.eng.fl_str_mv |
Copyright (c) 2018 ITECKNE |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
| rights_invalid_str_mv |
Copyright (c) 2018 ITECKNE http://purl.org/coar/access_right/c_abf2 |
| dc.format.mimetype.none.fl_str_mv |
application/pdf |
| dc.publisher.eng.fl_str_mv |
Universidad Santo Tomás. Seccional Bucaramanga |
| institution |
Universidad Santo Tomás |
| repository.name.fl_str_mv |
Repositorio Universidad Santo Tomás |
| repository.mail.fl_str_mv |
noreply@usta.edu.co |
| _version_ |
1800786387748782080 |