Algorithm for detection and diagnosis of industrial furnace faults applying singular value decomposition and graphic visualization

Detalhes bibliográficos
Autor(a) principal: Fonseca, Amanda Vilela
Data de Publicação: 2017
Outros Autores: Teófilo, Reinaldo Francisco, Soares, Vinícius Barroso, Silva, Deusanilde de Jesus
Tipo de documento: Artigo
Idioma: eng
Título da fonte: LOCUS Repositório Institucional da UFV
Texto Completo: https://doi.org/10.18540/jcecvl3iss7pp0920-0932
http://www.locus.ufv.br/handle/123456789/20104
Resumo: O desenvolvimento de um algoritmo baseado na decomposição dos valores singulares com visualização gráfica para auxiliar na detecção e no diagnóstico de falhas foi o objetivo deste trabalho. Para testar o algoritmo foram utilizados dados de temperatura reais de um forno industrial de uma unidade de processamento de gás natural. Nove detectores de temperatura foram monitorados no tempo. Além de uma falha real que gerou a parada do equipamento, foram também testadas cinco falhas simuladas nos detectores do forno. Os resultados mostraram que o algoritmo foi eficaz e possui grande potencial para auxiliar no monitoramento de processos industriais.
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spelling Fonseca, Amanda VilelaTeófilo, Reinaldo FranciscoSoares, Vinícius BarrosoSilva, Deusanilde de Jesus2018-06-14T13:47:35Z2018-06-14T13:47:35Z2017-11-2025271075https://doi.org/10.18540/jcecvl3iss7pp0920-0932http://www.locus.ufv.br/handle/123456789/20104O desenvolvimento de um algoritmo baseado na decomposição dos valores singulares com visualização gráfica para auxiliar na detecção e no diagnóstico de falhas foi o objetivo deste trabalho. Para testar o algoritmo foram utilizados dados de temperatura reais de um forno industrial de uma unidade de processamento de gás natural. Nove detectores de temperatura foram monitorados no tempo. Além de uma falha real que gerou a parada do equipamento, foram também testadas cinco falhas simuladas nos detectores do forno. Os resultados mostraram que o algoritmo foi eficaz e possui grande potencial para auxiliar no monitoramento de processos industriais.The development of an algorithm based on singular value decomposition with graphic visualization to aid in the fault detection and diagnosis was the aim of this work. In order to test the algorithm, real temperature data from an industrial furnace of a natural gas processing unit were used. Nine temperature detectors were monitored over time. In addition to a real fault that caused the shutdown of the equipment, five simulated faults in the furnace detectors were also tested. Results showed that the algorithm was effective and has great potential to assist in the monitoring of industrial processes.engThe Journal of Engineering and Exact Sciencesv. 03, n. 07, p. 0920-0932, Novembro 2017Detector failuresFault detection and diagnosisPrincipal component analysisSingular value decompositionAlgorithm for detection and diagnosis of industrial furnace faults applying singular value decomposition and graphic visualizationinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfinfo:eu-repo/semantics/openAccessreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALartigo.pdfartigo.pdftexto completoapplication/pdf815673https://locus.ufv.br//bitstream/123456789/20104/1/artigo.pdf54f0dc222973e6153f67a71660d33affMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://locus.ufv.br//bitstream/123456789/20104/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52THUMBNAILartigo.pdf.jpgartigo.pdf.jpgIM Thumbnailimage/jpeg4853https://locus.ufv.br//bitstream/123456789/20104/3/artigo.pdf.jpga77129568dcbfac695b7a5325a8efc63MD53123456789/201042018-06-14 23:00:45.461oai:locus.ufv.br:123456789/20104Tk9URTogUExBQ0UgWU9VUiBPV04gTElDRU5TRSBIRVJFClRoaXMgc2FtcGxlIGxpY2Vuc2UgaXMgcHJvdmlkZWQgZm9yIGluZm9ybWF0aW9uYWwgcHVycG9zZXMgb25seS4KCk5PTi1FWENMVVNJVkUgRElTVFJJQlVUSU9OIExJQ0VOU0UKCkJ5IHNpZ25pbmcgYW5kIHN1Ym1pdHRpbmcgdGhpcyBsaWNlbnNlLCB5b3UgKHRoZSBhdXRob3Iocykgb3IgY29weXJpZ2h0Cm93bmVyKSBncmFudHMgdG8gRFNwYWNlIFVuaXZlcnNpdHkgKERTVSkgdGhlIG5vbi1leGNsdXNpdmUgcmlnaHQgdG8gcmVwcm9kdWNlLAp0cmFuc2xhdGUgKGFzIGRlZmluZWQgYmVsb3cpLCBhbmQvb3IgZGlzdHJpYnV0ZSB5b3VyIHN1Ym1pc3Npb24gKGluY2x1ZGluZwp0aGUgYWJzdHJhY3QpIHdvcmxkd2lkZSBpbiBwcmludCBhbmQgZWxlY3Ryb25pYyBmb3JtYXQgYW5kIGluIGFueSBtZWRpdW0sCmluY2x1ZGluZyBidXQgbm90IGxpbWl0ZWQgdG8gYXVkaW8gb3IgdmlkZW8uCgpZb3UgYWdyZWUgdGhhdCBEU1UgbWF5LCB3aXRob3V0IGNoYW5naW5nIHRoZSBjb250ZW50LCB0cmFuc2xhdGUgdGhlCnN1Ym1pc3Npb24gdG8gYW55IG1lZGl1bSBvciBmb3JtYXQgZm9yIHRoZSBwdXJwb3NlIG9mIHByZXNlcnZhdGlvbi4KCllvdSBhbHNvIGFncmVlIHRoYXQgRFNVIG1heSBrZWVwIG1vcmUgdGhhbiBvbmUgY29weSBvZiB0aGlzIHN1Ym1pc3Npb24gZm9yCnB1cnBvc2VzIG9mIHNlY3VyaXR5LCBiYWNrLXVwIGFuZCBwcmVzZXJ2YXRpb24uCgpZb3UgcmVwcmVzZW50IHRoYXQgdGhlIHN1Ym1pc3Npb24gaXMgeW91ciBvcmlnaW5hbCB3b3JrLCBhbmQgdGhhdCB5b3UgaGF2ZQp0aGUgcmlnaHQgdG8gZ3JhbnQgdGhlIHJpZ2h0cyBjb250YWluZWQgaW4gdGhpcyBsaWNlbnNlLiBZb3UgYWxzbyByZXByZXNlbnQKdGhhdCB5b3VyIHN1Ym1pc3Npb24gZG9lcyBub3QsIHRvIHRoZSBiZXN0IG9mIHlvdXIga25vd2xlZGdlLCBpbmZyaW5nZSB1cG9uCmFueW9uZSdzIGNvcHlyaWdodC4KCklmIHRoZSBzdWJtaXNzaW9uIGNvbnRhaW5zIG1hdGVyaWFsIGZvciB3aGljaCB5b3UgZG8gbm90IGhvbGQgY29weXJpZ2h0LAp5b3UgcmVwcmVzZW50IHRoYXQgeW91IGhhdmUgb2J0YWluZWQgdGhlIHVucmVzdHJpY3RlZCBwZXJtaXNzaW9uIG9mIHRoZQpjb3B5cmlnaHQgb3duZXIgdG8gZ3JhbnQgRFNVIHRoZSByaWdodHMgcmVxdWlyZWQgYnkgdGhpcyBsaWNlbnNlLCBhbmQgdGhhdApzdWNoIHRoaXJkLXBhcnR5IG93bmVkIG1hdGVyaWFsIGlzIGNsZWFybHkgaWRlbnRpZmllZCBhbmQgYWNrbm93bGVkZ2VkCndpdGhpbiB0aGUgdGV4dCBvciBjb250ZW50IG9mIHRoZSBzdWJtaXNzaW9uLgoKSUYgVEhFIFNVQk1JU1NJT04gSVMgQkFTRUQgVVBPTiBXT1JLIFRIQVQgSEFTIEJFRU4gU1BPTlNPUkVEIE9SIFNVUFBPUlRFRApCWSBBTiBBR0VOQ1kgT1IgT1JHQU5JWkFUSU9OIE9USEVSIFRIQU4gRFNVLCBZT1UgUkVQUkVTRU5UIFRIQVQgWU9VIEhBVkUKRlVMRklMTEVEIEFOWSBSSUdIVCBPRiBSRVZJRVcgT1IgT1RIRVIgT0JMSUdBVElPTlMgUkVRVUlSRUQgQlkgU1VDSApDT05UUkFDVCBPUiBBR1JFRU1FTlQuCgpEU1Ugd2lsbCBjbGVhcmx5IGlkZW50aWZ5IHlvdXIgbmFtZShzKSBhcyB0aGUgYXV0aG9yKHMpIG9yIG93bmVyKHMpIG9mIHRoZQpzdWJtaXNzaW9uLCBhbmQgd2lsbCBub3QgbWFrZSBhbnkgYWx0ZXJhdGlvbiwgb3RoZXIgdGhhbiBhcyBhbGxvd2VkIGJ5IHRoaXMKbGljZW5zZSwgdG8geW91ciBzdWJtaXNzaW9uLgo=Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452018-06-15T02:00:45LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false
dc.title.en.fl_str_mv Algorithm for detection and diagnosis of industrial furnace faults applying singular value decomposition and graphic visualization
title Algorithm for detection and diagnosis of industrial furnace faults applying singular value decomposition and graphic visualization
spellingShingle Algorithm for detection and diagnosis of industrial furnace faults applying singular value decomposition and graphic visualization
Fonseca, Amanda Vilela
Detector failures
Fault detection and diagnosis
Principal component analysis
Singular value decomposition
title_short Algorithm for detection and diagnosis of industrial furnace faults applying singular value decomposition and graphic visualization
title_full Algorithm for detection and diagnosis of industrial furnace faults applying singular value decomposition and graphic visualization
title_fullStr Algorithm for detection and diagnosis of industrial furnace faults applying singular value decomposition and graphic visualization
title_full_unstemmed Algorithm for detection and diagnosis of industrial furnace faults applying singular value decomposition and graphic visualization
title_sort Algorithm for detection and diagnosis of industrial furnace faults applying singular value decomposition and graphic visualization
author Fonseca, Amanda Vilela
author_facet Fonseca, Amanda Vilela
Teófilo, Reinaldo Francisco
Soares, Vinícius Barroso
Silva, Deusanilde de Jesus
author_role author
author2 Teófilo, Reinaldo Francisco
Soares, Vinícius Barroso
Silva, Deusanilde de Jesus
author2_role author
author
author
dc.contributor.author.fl_str_mv Fonseca, Amanda Vilela
Teófilo, Reinaldo Francisco
Soares, Vinícius Barroso
Silva, Deusanilde de Jesus
dc.subject.pt-BR.fl_str_mv Detector failures
Fault detection and diagnosis
Principal component analysis
Singular value decomposition
topic Detector failures
Fault detection and diagnosis
Principal component analysis
Singular value decomposition
description O desenvolvimento de um algoritmo baseado na decomposição dos valores singulares com visualização gráfica para auxiliar na detecção e no diagnóstico de falhas foi o objetivo deste trabalho. Para testar o algoritmo foram utilizados dados de temperatura reais de um forno industrial de uma unidade de processamento de gás natural. Nove detectores de temperatura foram monitorados no tempo. Além de uma falha real que gerou a parada do equipamento, foram também testadas cinco falhas simuladas nos detectores do forno. Os resultados mostraram que o algoritmo foi eficaz e possui grande potencial para auxiliar no monitoramento de processos industriais.
publishDate 2017
dc.date.issued.fl_str_mv 2017-11-20
dc.date.accessioned.fl_str_mv 2018-06-14T13:47:35Z
dc.date.available.fl_str_mv 2018-06-14T13:47:35Z
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 https://doi.org/10.18540/jcecvl3iss7pp0920-0932
http://www.locus.ufv.br/handle/123456789/20104
dc.identifier.issn.none.fl_str_mv 25271075
identifier_str_mv 25271075
url https://doi.org/10.18540/jcecvl3iss7pp0920-0932
http://www.locus.ufv.br/handle/123456789/20104
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartofseries.pt-BR.fl_str_mv v. 03, n. 07, p. 0920-0932, Novembro 2017
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv The Journal of Engineering and Exact Sciences
publisher.none.fl_str_mv The Journal of Engineering and Exact Sciences
dc.source.none.fl_str_mv reponame:LOCUS Repositório Institucional da UFV
instname:Universidade Federal de Viçosa (UFV)
instacron:UFV
instname_str Universidade Federal de Viçosa (UFV)
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reponame_str LOCUS Repositório Institucional da UFV
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