Utilização de inteligência artificial para análise modal de uma viga engastada sob escoamento em túnel de vento

Detalhes bibliográficos
Autor(a) principal: Rodrigues, Pedro Augusto Dias
Data de Publicação: 2023
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Repositório Institucional da UFG
Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tede/12723
Resumo: Wind turbines suffer severe damage due to excessive wind loads or inadequate maintenance conditions, and catastrophic failures often occur causing huge losses. A structure, such as a wind turbine, can be monitored and evaluated through its modal characteristics, where natural frequencies, for example, are characteristics that are independent of operating conditions. They change only in case of damage, i.e. when stiffness and mass change. However, for the application of modal analysis, several sensors distributed in the structure are required, which involves high instrumentation costs. In view of this, it is proposed the use of modal analysis techniques integrated with virtual sensors, which, unlike real/physical sensors, are obtained through models. In this work, the virtual sensors are determined by using an artificial intelligence of the neural network type, which together with the modal analysis allows to obtain the modal characteristics: natural frequencies, modal shapes and damping. For this purpose, it is proposed to study a fixed Euler Bernoulli beam, an approximation model of a wind turbine, where the flow loads are generated through a wind tunnel with a speed controller. The flow velocities analyzed over the beam ranged from 10 to 20 m/s. The virtual sensor for operational modal analysis was modeled using a dynamic neural network where configurations of delay number and number of neurons in the hidden layer were investigated. In sequence, the modal characteristics of the Euler Bernoulli beam are compared using experimental modal analysis, situation in which the input is known and measured, and operational modal analysis, configuration where the input is unknown and not measured. For comparative analysis, the natural frequencies obtained in the different configurations and modal techniques showed good results when compared with the values of the Euler Bernoulli beam. For the modes, the Modal Assurance Criterion (MAC) was used, where when analyzing each independent result, the MAC returns excellent modal results, but when performing a comparative analysis of the different configurations and techniques, the MAC showed low correlation. Finally, the damping ratio showed an increase for higher flow velocities, but further investigations should be carried out in future works using other operational modal analysis techniques.
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spelling Fagundes Neto, Marlipe Garciahttp://lattes.cnpq.br/6303674803792521Kitatani Junior, Sigeohttp://lattes.cnpq.br/9419723461067210Fagundes Neto, Marlipe GarciaPena, José Luiz OliveiraColherinhas, Gino BertollucciKitatani Júnior, Sigeohttps://lattes.cnpq.br/2475910292073528Rodrigues, Pedro Augusto Dias2023-04-03T15:18:47Z2023-04-03T15:18:47Z2023-02-04RODRIGUES, P. A. D. Utilização de inteligência artificial para análise modal de uma viga engastada sob escoamento em túnel de vento. 2023. 102 f. Dissertação (Mestrado em Engenharia Mecânica) - Universidade Federal de Goiás, Goiânia, 2023.http://repositorio.bc.ufg.br/tede/handle/tede/12723ark:/38995/0013000004kpmWind turbines suffer severe damage due to excessive wind loads or inadequate maintenance conditions, and catastrophic failures often occur causing huge losses. A structure, such as a wind turbine, can be monitored and evaluated through its modal characteristics, where natural frequencies, for example, are characteristics that are independent of operating conditions. They change only in case of damage, i.e. when stiffness and mass change. However, for the application of modal analysis, several sensors distributed in the structure are required, which involves high instrumentation costs. In view of this, it is proposed the use of modal analysis techniques integrated with virtual sensors, which, unlike real/physical sensors, are obtained through models. In this work, the virtual sensors are determined by using an artificial intelligence of the neural network type, which together with the modal analysis allows to obtain the modal characteristics: natural frequencies, modal shapes and damping. For this purpose, it is proposed to study a fixed Euler Bernoulli beam, an approximation model of a wind turbine, where the flow loads are generated through a wind tunnel with a speed controller. The flow velocities analyzed over the beam ranged from 10 to 20 m/s. The virtual sensor for operational modal analysis was modeled using a dynamic neural network where configurations of delay number and number of neurons in the hidden layer were investigated. In sequence, the modal characteristics of the Euler Bernoulli beam are compared using experimental modal analysis, situation in which the input is known and measured, and operational modal analysis, configuration where the input is unknown and not measured. For comparative analysis, the natural frequencies obtained in the different configurations and modal techniques showed good results when compared with the values of the Euler Bernoulli beam. For the modes, the Modal Assurance Criterion (MAC) was used, where when analyzing each independent result, the MAC returns excellent modal results, but when performing a comparative analysis of the different configurations and techniques, the MAC showed low correlation. Finally, the damping ratio showed an increase for higher flow velocities, but further investigations should be carried out in future works using other operational modal analysis techniques.Os aerogeradores sofrem danos severos devido à carga de vento excessivas ou condições de manutenção inadequadas, e muitas vezes ocorrem falhas catastróficas causando prejuízos enormes. Uma estrutura, como o aerogerador, pode ser monitorada e avaliada por meio de suas características modais, onde as frequências naturais, por exemplo, são características que independem das condições de operação. Elas sofrem alterações somente em caso de danos, isto é, quando a rigidez e a massa sofrem alterações. No entanto, para aplicação da análise modal são necessários vários sensores distribuídos na estrutura, o que envolve custos elevados de instrumentação. Diante disso, é proposto a utilização de técnicas de análise modal integradas a sensores virtuais, que diferente dos sensores reais/físicos são obtidos por meio de modelos. Neste trabalho, os sensores virtuais são determinados por utilização de uma inteligência artificial do tipo rede neural, que em conjunto com a análise modal permite obter as características modais: frequências naturais, formas modais e amortecimento. Para tanto, propõe-se estudar uma viga de Euler Bernoulli engastada, modelo de aproximação de um aerogerador, onde as cargas de escoamento são geradas por meio de um túnel de vento com controlador de velocidade. As velocidades de escoamento analisadas sobre a viga foram de 10 a 20 m/s. O sensor virtual para análise modal operacional foi modelado utilizando rede neural dinâmica onde foram investigadas configurações de número de atraso e número de neurônios na camada oculta. Em sequência, são comparadas as características modais da viga de Euler Bernoulli utilizando análise modal experimental, situação em que a entrada em conhecida e mensurada, e análise modal operacional, configuração onde a entrada é desconhecida e não mensurada. Para análise comparativa, as frequências naturais obtidas nas diferentes configurações e técnicas modais apresentaram bons resultados ao comparar com os valores da viga de Euler Bernoulli. Para as formas modas utilizou-se o critério Modal assurance criterion (MAC), onde ao analisar cada resultado independente o MAC retorna excelentes resultados modais, porém ao realizar uma análise comparativa das diferentes configurações e técnicas o MAC apresentou baixa correlação. Por fim, a razão de amortecimento apresentou um aumento para maiores velocidades de escoamento, mas maiores investigações devem ser realizadas em trabalhos futuros utilizando outras técnicas de análise modal operacional.Submitted by Dayane Basílio (dayanebasilio@ufg.br) on 2023-03-30T14:46:54Z No. of bitstreams: 2 Dissertação - Pedro Augusto Dias Rodrigues - 2023.pdf: 4447804 bytes, checksum: 8c6c95e366a0799accde019d7ee238cc (MD5) license_rdf: 805 bytes, checksum: 4460e5956bc1d1639be9ae6146a50347 (MD5)Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2023-04-03T15:18:47Z (GMT) No. of bitstreams: 2 Dissertação - Pedro Augusto Dias Rodrigues - 2023.pdf: 4447804 bytes, checksum: 8c6c95e366a0799accde019d7ee238cc (MD5) license_rdf: 805 bytes, checksum: 4460e5956bc1d1639be9ae6146a50347 (MD5)Made available in DSpace on 2023-04-03T15:18:47Z (GMT). No. of bitstreams: 2 Dissertação - Pedro Augusto Dias Rodrigues - 2023.pdf: 4447804 bytes, checksum: 8c6c95e366a0799accde019d7ee238cc (MD5) license_rdf: 805 bytes, checksum: 4460e5956bc1d1639be9ae6146a50347 (MD5) Previous issue date: 2023-02-04porUniversidade Federal de GoiásPrograma de Pós-graduação em Engenharia MecânicaUFGBrasilEscola de Engenharia Elétrica, Mecânica e de Computação - EMC (RMG)Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessRede neuralTúnel de ventoViga de Euler BernoulliAnálise modalNeural networkWind tunnelEuler Bernoulli beammodal analysisENGENHARIAS::ENGENHARIA MECANICA::ENGENHARIA TERMICAUtilização de inteligência artificial para análise modal de uma viga engastada sob escoamento em túnel de ventoUse of artificial intelligence for modal analysis of a craned beam under flow in a wind tunnelinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesis465005005004443reponame:Repositório Institucional da UFGinstname:Universidade Federal de Goiás (UFG)instacron:UFGLICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://repositorio.bc.ufg.br/tede/bitstreams/b72a72be-8e13-420a-9b40-9f2631d48e73/download8a4605be74aa9ea9d79846c1fba20a33MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805http://repositorio.bc.ufg.br/tede/bitstreams/f72ac8e1-eab8-4b1c-a081-8cbd91fc40ad/download4460e5956bc1d1639be9ae6146a50347MD52ORIGINALDissertação - Pedro Augusto Dias Rodrigues - 2023.pdfDissertação - Pedro Augusto Dias Rodrigues - 2023.pdfapplication/pdf4447804http://repositorio.bc.ufg.br/tede/bitstreams/5bd0a875-32b3-407c-8251-5d9c32818176/download8c6c95e366a0799accde019d7ee238ccMD53tede/127232023-04-03 12:18:48.032http://creativecommons.org/licenses/by-nc-nd/4.0/Attribution-NonCommercial-NoDerivatives 4.0 Internationalopen.accessoai:repositorio.bc.ufg.br:tede/12723http://repositorio.bc.ufg.br/tedeRepositório InstitucionalPUBhttp://repositorio.bc.ufg.br/oai/requesttasesdissertacoes.bc@ufg.bropendoar:2023-04-03T15:18:48Repositório Institucional da UFG - Universidade Federal de Goiás (UFG)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
dc.title.pt_BR.fl_str_mv Utilização de inteligência artificial para análise modal de uma viga engastada sob escoamento em túnel de vento
dc.title.alternative.eng.fl_str_mv Use of artificial intelligence for modal analysis of a craned beam under flow in a wind tunnel
title Utilização de inteligência artificial para análise modal de uma viga engastada sob escoamento em túnel de vento
spellingShingle Utilização de inteligência artificial para análise modal de uma viga engastada sob escoamento em túnel de vento
Rodrigues, Pedro Augusto Dias
Rede neural
Túnel de vento
Viga de Euler Bernoulli
Análise modal
Neural network
Wind tunnel
Euler Bernoulli beam
modal analysis
ENGENHARIAS::ENGENHARIA MECANICA::ENGENHARIA TERMICA
title_short Utilização de inteligência artificial para análise modal de uma viga engastada sob escoamento em túnel de vento
title_full Utilização de inteligência artificial para análise modal de uma viga engastada sob escoamento em túnel de vento
title_fullStr Utilização de inteligência artificial para análise modal de uma viga engastada sob escoamento em túnel de vento
title_full_unstemmed Utilização de inteligência artificial para análise modal de uma viga engastada sob escoamento em túnel de vento
title_sort Utilização de inteligência artificial para análise modal de uma viga engastada sob escoamento em túnel de vento
author Rodrigues, Pedro Augusto Dias
author_facet Rodrigues, Pedro Augusto Dias
author_role author
dc.contributor.advisor1.fl_str_mv Fagundes Neto, Marlipe Garcia
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/6303674803792521
dc.contributor.advisor-co1.fl_str_mv Kitatani Junior, Sigeo
dc.contributor.advisor-co1Lattes.fl_str_mv http://lattes.cnpq.br/9419723461067210
dc.contributor.referee1.fl_str_mv Fagundes Neto, Marlipe Garcia
dc.contributor.referee2.fl_str_mv Pena, José Luiz Oliveira
dc.contributor.referee3.fl_str_mv Colherinhas, Gino Bertollucci
dc.contributor.referee4.fl_str_mv Kitatani Júnior, Sigeo
dc.contributor.authorLattes.fl_str_mv https://lattes.cnpq.br/2475910292073528
dc.contributor.author.fl_str_mv Rodrigues, Pedro Augusto Dias
contributor_str_mv Fagundes Neto, Marlipe Garcia
Kitatani Junior, Sigeo
Fagundes Neto, Marlipe Garcia
Pena, José Luiz Oliveira
Colherinhas, Gino Bertollucci
Kitatani Júnior, Sigeo
dc.subject.por.fl_str_mv Rede neural
Túnel de vento
Viga de Euler Bernoulli
Análise modal
topic Rede neural
Túnel de vento
Viga de Euler Bernoulli
Análise modal
Neural network
Wind tunnel
Euler Bernoulli beam
modal analysis
ENGENHARIAS::ENGENHARIA MECANICA::ENGENHARIA TERMICA
dc.subject.eng.fl_str_mv Neural network
Wind tunnel
Euler Bernoulli beam
modal analysis
dc.subject.cnpq.fl_str_mv ENGENHARIAS::ENGENHARIA MECANICA::ENGENHARIA TERMICA
description Wind turbines suffer severe damage due to excessive wind loads or inadequate maintenance conditions, and catastrophic failures often occur causing huge losses. A structure, such as a wind turbine, can be monitored and evaluated through its modal characteristics, where natural frequencies, for example, are characteristics that are independent of operating conditions. They change only in case of damage, i.e. when stiffness and mass change. However, for the application of modal analysis, several sensors distributed in the structure are required, which involves high instrumentation costs. In view of this, it is proposed the use of modal analysis techniques integrated with virtual sensors, which, unlike real/physical sensors, are obtained through models. In this work, the virtual sensors are determined by using an artificial intelligence of the neural network type, which together with the modal analysis allows to obtain the modal characteristics: natural frequencies, modal shapes and damping. For this purpose, it is proposed to study a fixed Euler Bernoulli beam, an approximation model of a wind turbine, where the flow loads are generated through a wind tunnel with a speed controller. The flow velocities analyzed over the beam ranged from 10 to 20 m/s. The virtual sensor for operational modal analysis was modeled using a dynamic neural network where configurations of delay number and number of neurons in the hidden layer were investigated. In sequence, the modal characteristics of the Euler Bernoulli beam are compared using experimental modal analysis, situation in which the input is known and measured, and operational modal analysis, configuration where the input is unknown and not measured. For comparative analysis, the natural frequencies obtained in the different configurations and modal techniques showed good results when compared with the values of the Euler Bernoulli beam. For the modes, the Modal Assurance Criterion (MAC) was used, where when analyzing each independent result, the MAC returns excellent modal results, but when performing a comparative analysis of the different configurations and techniques, the MAC showed low correlation. Finally, the damping ratio showed an increase for higher flow velocities, but further investigations should be carried out in future works using other operational modal analysis techniques.
publishDate 2023
dc.date.accessioned.fl_str_mv 2023-04-03T15:18:47Z
dc.date.available.fl_str_mv 2023-04-03T15:18:47Z
dc.date.issued.fl_str_mv 2023-02-04
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv RODRIGUES, P. A. D. Utilização de inteligência artificial para análise modal de uma viga engastada sob escoamento em túnel de vento. 2023. 102 f. Dissertação (Mestrado em Engenharia Mecânica) - Universidade Federal de Goiás, Goiânia, 2023.
dc.identifier.uri.fl_str_mv http://repositorio.bc.ufg.br/tede/handle/tede/12723
dc.identifier.dark.fl_str_mv ark:/38995/0013000004kpm
identifier_str_mv RODRIGUES, P. A. D. Utilização de inteligência artificial para análise modal de uma viga engastada sob escoamento em túnel de vento. 2023. 102 f. Dissertação (Mestrado em Engenharia Mecânica) - Universidade Federal de Goiás, Goiânia, 2023.
ark:/38995/0013000004kpm
url http://repositorio.bc.ufg.br/tede/handle/tede/12723
dc.language.iso.fl_str_mv por
language por
dc.relation.program.fl_str_mv 46
dc.relation.confidence.fl_str_mv 500
500
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dc.relation.department.fl_str_mv 4
dc.relation.cnpq.fl_str_mv 443
dc.rights.driver.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Universidade Federal de Goiás
dc.publisher.program.fl_str_mv Programa de Pós-graduação em Engenharia Mecânica
dc.publisher.initials.fl_str_mv UFG
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv Escola de Engenharia Elétrica, Mecânica e de Computação - EMC (RMG)
publisher.none.fl_str_mv Universidade Federal de Goiás
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFG
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