The application of a two-step AI model to an automated pneumatic drilling process

Real-world processes may be improved through a combination of artificial intelligence and identification techniques. This work presents a multidisciplinary study that identifies and applies unsupervised connectionist models in conjunction with modelling systems. This particular industrial problem is...

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Detalles Bibliográficos
Autores: Sedano Franco, Javier, Corchado Rodríguez, Emilio Santiago, Curiel, Leticia, Villar Flecha, José R., Bravo Díez, Pedro M.
Tipo de recurso: artículo
Fecha de publicación:2009
País:España
Institución:Universidad de Salamanca (USAL)
Repositorio:GREDOS. Repositorio Institucional de la Universidad de Salamanca
OAI Identifier:oai:gredos.usal.es:10366/134426
Acceso en línea:http://hdl.handle.net/10366/134426
Access Level:acceso abierto
Palabra clave:Computer Science
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spelling The application of a two-step AI model to an automated pneumatic drilling processSedano Franco, JavierCorchado Rodríguez, Emilio SantiagoCuriel, LeticiaVillar Flecha, José R.Bravo Díez, Pedro M.Computer ScienceReal-world processes may be improved through a combination of artificial intelligence and identification techniques. This work presents a multidisciplinary study that identifies and applies unsupervised connectionist models in conjunction with modelling systems. This particular industrial problem is defined by a data set relayed through sensors situated on a robotic drill used in the construction of industrial storage centres. The first step entails determination of the most relevant structures in the data set with the application of the connectionist architectures. The second step combines the results of the first one to identify a model for the optimal working conditions of the drilling robot that is based on low-order models such as black box that approximate the optimal form of the model. Finally, it is shown that the most appropriate model to control these industrial tasks is the Box-Jenkins algorithm, which calculates the function of a linear system from its input and output samples.Informa UK Limited201720172009info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10366/134426reponame:GREDOS. Repositorio Institucional de la Universidad de Salamancainstname:Universidad de Salamanca (USAL)InglésAttribution-NonCommercial-NoDerivs 3.0 Unportedhttps://creativecommons.org/licenses/by-nc-nd/3.0/info:eu-repo/semantics/openAccessoai:gredos.usal.es:10366/1344262026-06-07T06:28:51Z
dc.title.none.fl_str_mv The application of a two-step AI model to an automated pneumatic drilling process
title The application of a two-step AI model to an automated pneumatic drilling process
spellingShingle The application of a two-step AI model to an automated pneumatic drilling process
Sedano Franco, Javier
Computer Science
title_short The application of a two-step AI model to an automated pneumatic drilling process
title_full The application of a two-step AI model to an automated pneumatic drilling process
title_fullStr The application of a two-step AI model to an automated pneumatic drilling process
title_full_unstemmed The application of a two-step AI model to an automated pneumatic drilling process
title_sort The application of a two-step AI model to an automated pneumatic drilling process
dc.creator.none.fl_str_mv Sedano Franco, Javier
Corchado Rodríguez, Emilio Santiago
Curiel, Leticia
Villar Flecha, José R.
Bravo Díez, Pedro M.
author Sedano Franco, Javier
author_facet Sedano Franco, Javier
Corchado Rodríguez, Emilio Santiago
Curiel, Leticia
Villar Flecha, José R.
Bravo Díez, Pedro M.
author_role author
author2 Corchado Rodríguez, Emilio Santiago
Curiel, Leticia
Villar Flecha, José R.
Bravo Díez, Pedro M.
author2_role author
author
author
author
dc.subject.none.fl_str_mv Computer Science
topic Computer Science
description Real-world processes may be improved through a combination of artificial intelligence and identification techniques. This work presents a multidisciplinary study that identifies and applies unsupervised connectionist models in conjunction with modelling systems. This particular industrial problem is defined by a data set relayed through sensors situated on a robotic drill used in the construction of industrial storage centres. The first step entails determination of the most relevant structures in the data set with the application of the connectionist architectures. The second step combines the results of the first one to identify a model for the optimal working conditions of the drilling robot that is based on low-order models such as black box that approximate the optimal form of the model. Finally, it is shown that the most appropriate model to control these industrial tasks is the Box-Jenkins algorithm, which calculates the function of a linear system from its input and output samples.
publishDate 2009
dc.date.none.fl_str_mv 2009
2017
2017
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10366/134426
url http://hdl.handle.net/10366/134426
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv Attribution-NonCommercial-NoDerivs 3.0 Unported
https://creativecommons.org/licenses/by-nc-nd/3.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivs 3.0 Unported
https://creativecommons.org/licenses/by-nc-nd/3.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Informa UK Limited
publisher.none.fl_str_mv Informa UK Limited
dc.source.none.fl_str_mv reponame:GREDOS. Repositorio Institucional de la Universidad de Salamanca
instname:Universidad de Salamanca (USAL)
instname_str Universidad de Salamanca (USAL)
reponame_str GREDOS. Repositorio Institucional de la Universidad de Salamanca
collection GREDOS. Repositorio Institucional de la Universidad de Salamanca
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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