Neural approach for induction motor load torque identification in industrial applications

Detalhes bibliográficos
Autor(a) principal: Goedtel, Alessandro
Data de Publicação: 2007
Outros Autores: Da Silva, Ivan N., Serni, Paulo J. A. [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/CCA.2007.4389277
http://hdl.handle.net/11449/225153
Resumo: Induction motors are widely used in several industrial sectors. However, the dimensioning of induction motors is often inaccurate because, in most cases, the load behavior in the shan is completely unknown. The proposal of this paper is to use artificial neural networks as a tool for dimensioning induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Since the proposed approach uses current, voltage and speed values as the only input parameters, one of its potentialities is related to the facility of hardware implementation for industrial environments and field applications. Simulation results are also presented to validate the proposed approach. © 2007 IEEE.
id UNSP_597a095aaec75a5899a938898a32290a
oai_identifier_str oai:repositorio.unesp.br:11449/225153
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling Neural approach for induction motor load torque identification in industrial applicationsInduction motors are widely used in several industrial sectors. However, the dimensioning of induction motors is often inaccurate because, in most cases, the load behavior in the shan is completely unknown. The proposal of this paper is to use artificial neural networks as a tool for dimensioning induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Since the proposed approach uses current, voltage and speed values as the only input parameters, one of its potentialities is related to the facility of hardware implementation for industrial environments and field applications. Simulation results are also presented to validate the proposed approach. © 2007 IEEE.IEEEElectrical Engineering Department (EESC) University of São Paulo (USP), Av. Trabalhador Sancarlense, 400, CEP 13566-590, São Carlos, SPElectrical Engineering Department (DEE) State University of São Paulo (UNESP), CP 473, CEP 17033-360, Bauru, SPElectrical Engineering Department (DEE) State University of São Paulo (UNESP), CP 473, CEP 17033-360, Bauru, SPIEEEUniversidade de São Paulo (USP)Universidade Estadual Paulista (UNESP)Goedtel, AlessandroDa Silva, Ivan N.Serni, Paulo J. A. [UNESP]2022-04-28T20:40:14Z2022-04-28T20:40:14Z2007-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject479-484http://dx.doi.org/10.1109/CCA.2007.4389277Proceedings of the IEEE International Conference on Control Applications, p. 479-484.http://hdl.handle.net/11449/22515310.1109/CCA.2007.43892772-s2.0-43049164373Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of the IEEE International Conference on Control Applicationsinfo:eu-repo/semantics/openAccess2024-06-28T13:34:35Zoai:repositorio.unesp.br:11449/225153Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:21:01.554576Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Neural approach for induction motor load torque identification in industrial applications
title Neural approach for induction motor load torque identification in industrial applications
spellingShingle Neural approach for induction motor load torque identification in industrial applications
Goedtel, Alessandro
title_short Neural approach for induction motor load torque identification in industrial applications
title_full Neural approach for induction motor load torque identification in industrial applications
title_fullStr Neural approach for induction motor load torque identification in industrial applications
title_full_unstemmed Neural approach for induction motor load torque identification in industrial applications
title_sort Neural approach for induction motor load torque identification in industrial applications
author Goedtel, Alessandro
author_facet Goedtel, Alessandro
Da Silva, Ivan N.
Serni, Paulo J. A. [UNESP]
author_role author
author2 Da Silva, Ivan N.
Serni, Paulo J. A. [UNESP]
author2_role author
author
dc.contributor.none.fl_str_mv IEEE
Universidade de São Paulo (USP)
Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Goedtel, Alessandro
Da Silva, Ivan N.
Serni, Paulo J. A. [UNESP]
description Induction motors are widely used in several industrial sectors. However, the dimensioning of induction motors is often inaccurate because, in most cases, the load behavior in the shan is completely unknown. The proposal of this paper is to use artificial neural networks as a tool for dimensioning induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Since the proposed approach uses current, voltage and speed values as the only input parameters, one of its potentialities is related to the facility of hardware implementation for industrial environments and field applications. Simulation results are also presented to validate the proposed approach. © 2007 IEEE.
publishDate 2007
dc.date.none.fl_str_mv 2007-12-01
2022-04-28T20:40:14Z
2022-04-28T20:40:14Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/CCA.2007.4389277
Proceedings of the IEEE International Conference on Control Applications, p. 479-484.
http://hdl.handle.net/11449/225153
10.1109/CCA.2007.4389277
2-s2.0-43049164373
url http://dx.doi.org/10.1109/CCA.2007.4389277
http://hdl.handle.net/11449/225153
identifier_str_mv Proceedings of the IEEE International Conference on Control Applications, p. 479-484.
10.1109/CCA.2007.4389277
2-s2.0-43049164373
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Proceedings of the IEEE International Conference on Control Applications
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 479-484
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1808128795617525760

Registros relacionados