Reliability analysis using experimental statistical methods and ais: Application in continuous flow tubes of gaseous medium
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.4025/ACTASCITECHNOL.V43I1.55825 http://hdl.handle.net/11449/233902 |
Resumo: | The motivation for the development of this work arose from the observation of maintenance in pressure vessels, which are categorized as highly hazardous security risk products. The costs of detecting failures in the production systems allow the result of the process to be safe and of good quality, using standardized tests internally within the company. The main objective of this work demonstrates the efficiency and robustness of the artificial immune system (AIS) of negative selection in the detection of failures by recognizing the vibration signals and categorizing them in the degree of probability and level of severity of failures. The intrinsic objectives are the application of the elimination of signal noise by the Wiener filter, and the processing of data-Wiener data using experimental statistics. The result of this work successfully demonstrates the precision between the experimental statistical and AIS techniques of negative selection; the robustness of the algorithm in precision and signal recognition; and the classification of the degree of severity and probability of failure. |
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Reliability analysis using experimental statistical methods and ais: Application in continuous flow tubes of gaseous mediumArtificial immune systemsExperimental statistical methodsFlow tubesNegative selection algorithmStructural health monitoringThe motivation for the development of this work arose from the observation of maintenance in pressure vessels, which are categorized as highly hazardous security risk products. The costs of detecting failures in the production systems allow the result of the process to be safe and of good quality, using standardized tests internally within the company. The main objective of this work demonstrates the efficiency and robustness of the artificial immune system (AIS) of negative selection in the detection of failures by recognizing the vibration signals and categorizing them in the degree of probability and level of severity of failures. The intrinsic objectives are the application of the elimination of signal noise by the Wiener filter, and the processing of data-Wiener data using experimental statistics. The result of this work successfully demonstrates the precision between the experimental statistical and AIS techniques of negative selection; the robustness of the algorithm in precision and signal recognition; and the classification of the degree of severity and probability of failure.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Departamento de Biocombustíveis Fatec Fernando Amaral de Almeida Prado, São PauloDepartamento de Engenharia Física e Matemática Instituto de Química Universidade Estadual Paulista “Júlio de Mesquita Filho”, Rua Prof. Francisco Degni, 55, Quitandinha, São PauloDepartamento de Engenharia Mecânica Universidade Estadual Paulista “Júlio de Mesquita Filho”, São PauloDepartamento de Processo de Soldagem Faculdade de Tecnologia Itaquera Miguel Reale, São PauloDepartment of Mathematics Indira Gandhi National Tribal University, Madhya PradeshDepartamento de Engenharia e Ciências Exatas Universidade Estadual Paulista “Júlio Mesquita Filho”, São PauloDepartment of Mathematics School of Advanced Sciences Vellore Institute of Technology, Tamil NaduDepartamento de Engenharia Física e Matemática Instituto de Química Universidade Estadual Paulista “Júlio de Mesquita Filho”, Rua Prof. Francisco Degni, 55, Quitandinha, São PauloDepartamento de Engenharia Mecânica Universidade Estadual Paulista “Júlio de Mesquita Filho”, São PauloDepartamento de Engenharia e Ciências Exatas Universidade Estadual Paulista “Júlio Mesquita Filho”, São PauloFAPESP: 2019 / 10515-4Fatec Fernando Amaral de Almeida PradoUniversidade Estadual Paulista (UNESP)Faculdade de Tecnologia Itaquera Miguel RealeIndira Gandhi National Tribal UniversityVellore Institute of TechnologyOuta, RobertoChavarette, Fábio Roberto [UNESP]Gonçalves, Aparecido Carlos [UNESP]da Silva, Sidney LealMishra, Vishnu NarayanPanosso, Alan Rodrigo [UNESP]Mishra, Lakshmi Narayan2022-05-01T11:23:37Z2022-05-01T11:23:37Z2021-08-20info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.4025/ACTASCITECHNOL.V43I1.55825Acta Scientiarum - Technology, v. 43.1807-86641806-2563http://hdl.handle.net/11449/23390210.4025/ACTASCITECHNOL.V43I1.558252-s2.0-85121286741Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengActa Scientiarum - Technologyinfo:eu-repo/semantics/openAccess2022-05-01T11:23:37Zoai:repositorio.unesp.br:11449/233902Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-05-01T11:23:37Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Reliability analysis using experimental statistical methods and ais: Application in continuous flow tubes of gaseous medium |
title |
Reliability analysis using experimental statistical methods and ais: Application in continuous flow tubes of gaseous medium |
spellingShingle |
Reliability analysis using experimental statistical methods and ais: Application in continuous flow tubes of gaseous medium Outa, Roberto Artificial immune systems Experimental statistical methods Flow tubes Negative selection algorithm Structural health monitoring |
title_short |
Reliability analysis using experimental statistical methods and ais: Application in continuous flow tubes of gaseous medium |
title_full |
Reliability analysis using experimental statistical methods and ais: Application in continuous flow tubes of gaseous medium |
title_fullStr |
Reliability analysis using experimental statistical methods and ais: Application in continuous flow tubes of gaseous medium |
title_full_unstemmed |
Reliability analysis using experimental statistical methods and ais: Application in continuous flow tubes of gaseous medium |
title_sort |
Reliability analysis using experimental statistical methods and ais: Application in continuous flow tubes of gaseous medium |
author |
Outa, Roberto |
author_facet |
Outa, Roberto Chavarette, Fábio Roberto [UNESP] Gonçalves, Aparecido Carlos [UNESP] da Silva, Sidney Leal Mishra, Vishnu Narayan Panosso, Alan Rodrigo [UNESP] Mishra, Lakshmi Narayan |
author_role |
author |
author2 |
Chavarette, Fábio Roberto [UNESP] Gonçalves, Aparecido Carlos [UNESP] da Silva, Sidney Leal Mishra, Vishnu Narayan Panosso, Alan Rodrigo [UNESP] Mishra, Lakshmi Narayan |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Fatec Fernando Amaral de Almeida Prado Universidade Estadual Paulista (UNESP) Faculdade de Tecnologia Itaquera Miguel Reale Indira Gandhi National Tribal University Vellore Institute of Technology |
dc.contributor.author.fl_str_mv |
Outa, Roberto Chavarette, Fábio Roberto [UNESP] Gonçalves, Aparecido Carlos [UNESP] da Silva, Sidney Leal Mishra, Vishnu Narayan Panosso, Alan Rodrigo [UNESP] Mishra, Lakshmi Narayan |
dc.subject.por.fl_str_mv |
Artificial immune systems Experimental statistical methods Flow tubes Negative selection algorithm Structural health monitoring |
topic |
Artificial immune systems Experimental statistical methods Flow tubes Negative selection algorithm Structural health monitoring |
description |
The motivation for the development of this work arose from the observation of maintenance in pressure vessels, which are categorized as highly hazardous security risk products. The costs of detecting failures in the production systems allow the result of the process to be safe and of good quality, using standardized tests internally within the company. The main objective of this work demonstrates the efficiency and robustness of the artificial immune system (AIS) of negative selection in the detection of failures by recognizing the vibration signals and categorizing them in the degree of probability and level of severity of failures. The intrinsic objectives are the application of the elimination of signal noise by the Wiener filter, and the processing of data-Wiener data using experimental statistics. The result of this work successfully demonstrates the precision between the experimental statistical and AIS techniques of negative selection; the robustness of the algorithm in precision and signal recognition; and the classification of the degree of severity and probability of failure. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-08-20 2022-05-01T11:23:37Z 2022-05-01T11:23:37Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.4025/ACTASCITECHNOL.V43I1.55825 Acta Scientiarum - Technology, v. 43. 1807-8664 1806-2563 http://hdl.handle.net/11449/233902 10.4025/ACTASCITECHNOL.V43I1.55825 2-s2.0-85121286741 |
url |
http://dx.doi.org/10.4025/ACTASCITECHNOL.V43I1.55825 http://hdl.handle.net/11449/233902 |
identifier_str_mv |
Acta Scientiarum - Technology, v. 43. 1807-8664 1806-2563 10.4025/ACTASCITECHNOL.V43I1.55825 2-s2.0-85121286741 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Acta Scientiarum - Technology |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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_ |
1803046635785158656 |