Prognosis and Detection of Experimental Failures in Open Field Diesel Engines Applying Wienerˈs Artificial Immunological Systems
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/10.22055/jacm.2020.34972.2525 http://hdl.handle.net/11449/207558 |
Resumo: | The high costs of open-field diesel engines arise from the lack of maintenance of these systems. Thus, the maintenance of this equipment has been treated as a great challenge, as some methods of data monitoring are not possible to be implemented, given the inadequate sensing conditions, plant location, local climate, facilities, even the methods and maintenance routines. In a second step, the labor is not qualified and of sufficient quantity to meet the demand, resulting in a slow and inefficient system. One of the challenges of predictive systems is to inform damage and failures in real time of the operating conditions of these machines and equipment. This work demonstrates the possibility of analyzing and detecting failures in open field predictive systems, using the concepts of vibration and acoustics in artificial intelligence. One of the results of this work demonstrates the robustness of the negative selection artificial immune system algorithm, whose application of the Wiener filter was of fundamental need. The other result demonstrates the versatility of conditioned use both or just one of the concepts between vibration and acoustics, in prognosis and fault detection. Considering the versatility of using these two techniques, it is possible to affirm that, the predictive systems of real time analysis have an effective solution directed to the area and, if implemented, it is of low cost and high efficiency. |
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Prognosis and Detection of Experimental Failures in Open Field Diesel Engines Applying Wienerˈs Artificial Immunological SystemsAcousticsAIS-negative selectionPredictive systemVibrationWiener filterThe high costs of open-field diesel engines arise from the lack of maintenance of these systems. Thus, the maintenance of this equipment has been treated as a great challenge, as some methods of data monitoring are not possible to be implemented, given the inadequate sensing conditions, plant location, local climate, facilities, even the methods and maintenance routines. In a second step, the labor is not qualified and of sufficient quantity to meet the demand, resulting in a slow and inefficient system. One of the challenges of predictive systems is to inform damage and failures in real time of the operating conditions of these machines and equipment. This work demonstrates the possibility of analyzing and detecting failures in open field predictive systems, using the concepts of vibration and acoustics in artificial intelligence. One of the results of this work demonstrates the robustness of the negative selection artificial immune system algorithm, whose application of the Wiener filter was of fundamental need. The other result demonstrates the versatility of conditioned use both or just one of the concepts between vibration and acoustics, in prognosis and fault detection. Considering the versatility of using these two techniques, it is possible to affirm that, the predictive systems of real time analysis have an effective solution directed to the area and, if implemented, it is of low cost and high efficiency.Faculty of Technology of Araçatuba Department of Biofuels, Av. Prestes Maia, 1764 - IpanemaUNESP - Instituto de Química Department of Engenharia Física e Matemática, Rua Prof. Francisco Degni, 55 – QuitandinhaFaculty of Technology of Catanduva Department of Automação Indusrial, Av. Rua Maranhão, 898 - CentroUNESP - Univ. Estadual Paulista Faculty of Engineering of Ilha Solteira Department of Mechanical EngineeringUNESP - Instituto de Química Department of Engenharia Física e Matemática, Rua Prof. Francisco Degni, 55 – QuitandinhaUNESP - Univ. Estadual Paulista Faculty of Engineering of Ilha Solteira Department of Mechanical EngineeringFaculty of Technology of AraçatubaUniversidade Estadual Paulista (Unesp)Faculty of Technology of CatanduvaOuta, RobertoChavarette, Fábio Roberto [UNESP]Toro, Paulo FernandoGonçalves, Aparecido Carlos [UNESP]Santos, Lucas Henrique dos [UNESP]2021-06-25T10:57:16Z2021-06-25T10:57:16Z2021-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article1-12http://dx.doi.org/10.22055/jacm.2020.34972.2525Journal of Applied and Computational Mechanics, v. 7, n. 1, p. 1-12, 2021.2383-4536http://hdl.handle.net/11449/20755810.22055/jacm.2020.34972.25252-s2.0-85103644246Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of Applied and Computational Mechanicsinfo:eu-repo/semantics/openAccess2024-07-04T20:06:06Zoai:repositorio.unesp.br:11449/207558Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:14:46.100807Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Prognosis and Detection of Experimental Failures in Open Field Diesel Engines Applying Wienerˈs Artificial Immunological Systems |
title |
Prognosis and Detection of Experimental Failures in Open Field Diesel Engines Applying Wienerˈs Artificial Immunological Systems |
spellingShingle |
Prognosis and Detection of Experimental Failures in Open Field Diesel Engines Applying Wienerˈs Artificial Immunological Systems Outa, Roberto Acoustics AIS-negative selection Predictive system Vibration Wiener filter |
title_short |
Prognosis and Detection of Experimental Failures in Open Field Diesel Engines Applying Wienerˈs Artificial Immunological Systems |
title_full |
Prognosis and Detection of Experimental Failures in Open Field Diesel Engines Applying Wienerˈs Artificial Immunological Systems |
title_fullStr |
Prognosis and Detection of Experimental Failures in Open Field Diesel Engines Applying Wienerˈs Artificial Immunological Systems |
title_full_unstemmed |
Prognosis and Detection of Experimental Failures in Open Field Diesel Engines Applying Wienerˈs Artificial Immunological Systems |
title_sort |
Prognosis and Detection of Experimental Failures in Open Field Diesel Engines Applying Wienerˈs Artificial Immunological Systems |
author |
Outa, Roberto |
author_facet |
Outa, Roberto Chavarette, Fábio Roberto [UNESP] Toro, Paulo Fernando Gonçalves, Aparecido Carlos [UNESP] Santos, Lucas Henrique dos [UNESP] |
author_role |
author |
author2 |
Chavarette, Fábio Roberto [UNESP] Toro, Paulo Fernando Gonçalves, Aparecido Carlos [UNESP] Santos, Lucas Henrique dos [UNESP] |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Faculty of Technology of Araçatuba Universidade Estadual Paulista (Unesp) Faculty of Technology of Catanduva |
dc.contributor.author.fl_str_mv |
Outa, Roberto Chavarette, Fábio Roberto [UNESP] Toro, Paulo Fernando Gonçalves, Aparecido Carlos [UNESP] Santos, Lucas Henrique dos [UNESP] |
dc.subject.por.fl_str_mv |
Acoustics AIS-negative selection Predictive system Vibration Wiener filter |
topic |
Acoustics AIS-negative selection Predictive system Vibration Wiener filter |
description |
The high costs of open-field diesel engines arise from the lack of maintenance of these systems. Thus, the maintenance of this equipment has been treated as a great challenge, as some methods of data monitoring are not possible to be implemented, given the inadequate sensing conditions, plant location, local climate, facilities, even the methods and maintenance routines. In a second step, the labor is not qualified and of sufficient quantity to meet the demand, resulting in a slow and inefficient system. One of the challenges of predictive systems is to inform damage and failures in real time of the operating conditions of these machines and equipment. This work demonstrates the possibility of analyzing and detecting failures in open field predictive systems, using the concepts of vibration and acoustics in artificial intelligence. One of the results of this work demonstrates the robustness of the negative selection artificial immune system algorithm, whose application of the Wiener filter was of fundamental need. The other result demonstrates the versatility of conditioned use both or just one of the concepts between vibration and acoustics, in prognosis and fault detection. Considering the versatility of using these two techniques, it is possible to affirm that, the predictive systems of real time analysis have an effective solution directed to the area and, if implemented, it is of low cost and high efficiency. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-06-25T10:57:16Z 2021-06-25T10:57:16Z 2021-12-01 |
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/10.22055/jacm.2020.34972.2525 Journal of Applied and Computational Mechanics, v. 7, n. 1, p. 1-12, 2021. 2383-4536 http://hdl.handle.net/11449/207558 10.22055/jacm.2020.34972.2525 2-s2.0-85103644246 |
url |
http://dx.doi.org/10.22055/jacm.2020.34972.2525 http://hdl.handle.net/11449/207558 |
identifier_str_mv |
Journal of Applied and Computational Mechanics, v. 7, n. 1, p. 1-12, 2021. 2383-4536 10.22055/jacm.2020.34972.2525 2-s2.0-85103644246 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Journal of Applied and Computational Mechanics |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
1-12 |
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_ |
1808128778722869248 |