Reliability analysis using experimental statistical methods and ais: Application in continuous flow tubes of gaseous medium

Detalhes bibliográficos
Autor(a) principal: Outa, Roberto
Data de Publicação: 2021
Outros Autores: Chavarette, Fábio Roberto [UNESP], Gonçalves, Aparecido Carlos [UNESP], da Silva, Sidney Leal, Mishra, Vishnu Narayan, Panosso, Alan Rodrigo [UNESP], Mishra, Lakshmi Narayan
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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spelling 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
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