Plantwide periodical disturbances isolation and elimination in a petrochemical unit

Detalhes bibliográficos
Autor(a) principal: Farenzena, Marcelo
Data de Publicação: 2015
Outros Autores: Kayser, Cristine Alessandra, Trierweiler, Jorge Otávio
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/142315
Resumo: Reducing process variability is crucial to reach a more profitable operating point. Periodical disturbances, however, impose barriers to achieve this goal. Their effect can be strong since one disturbance that appears in a specific loop of a highly coupled plant can be seen in several loops. Thus, isolating their source and diagnosing their cause are essential. In this work, we describe the application of spectral independent component analysis to isolate a periodical disturbance that has a strong impact on the final variability in a polyethylene plant located in Southern Brazil. After the first analysis, the source was detected and the cause identified: valve stiction. To identify the cause (valve, bad tuning, or periodic disturbance), we used the methodology based on higher-order statistics. Once the valve problem had been overcome, the product variance was reduced by 93%.
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spelling Farenzena, MarceloKayser, Cristine AlessandraTrierweiler, Jorge Otávio2016-06-08T02:09:16Z20150104-6632http://hdl.handle.net/10183/142315000992301Reducing process variability is crucial to reach a more profitable operating point. Periodical disturbances, however, impose barriers to achieve this goal. Their effect can be strong since one disturbance that appears in a specific loop of a highly coupled plant can be seen in several loops. Thus, isolating their source and diagnosing their cause are essential. In this work, we describe the application of spectral independent component analysis to isolate a periodical disturbance that has a strong impact on the final variability in a polyethylene plant located in Southern Brazil. After the first analysis, the source was detected and the cause identified: valve stiction. To identify the cause (valve, bad tuning, or periodic disturbance), we used the methodology based on higher-order statistics. Once the valve problem had been overcome, the product variance was reduced by 93%.application/pdfporBrazilian journal of chemical engineering. São Paulo, SP. Vol. 32, no. 4 (Oct./Dec. 2015), p. 919-927Diagnóstico de falhasVálvulas (Engenharia)Análise espectralFault diagnosisPlant-wide disturbanceOscillationIndependent Component AnalysisPlantwide periodical disturbances isolation and elimination in a petrochemical unitinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/otherinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSORIGINAL000992301.pdf000992301.pdfTexto completoapplication/pdf1064423http://www.lume.ufrgs.br/bitstream/10183/142315/1/000992301.pdf68a0a86cabc803a4276d90890b88c8ccMD51TEXT000992301.pdf.txt000992301.pdf.txtExtracted Texttext/plain29889http://www.lume.ufrgs.br/bitstream/10183/142315/2/000992301.pdf.txt6b274da8eb2a9dfda54011d932de55c4MD52THUMBNAIL000992301.pdf.jpg000992301.pdf.jpgGenerated Thumbnailimage/jpeg1804http://www.lume.ufrgs.br/bitstream/10183/142315/3/000992301.pdf.jpgd5c7ad9dc91767699dc04751bf5c6dbcMD5310183/1423152018-10-26 09:45:43.576oai:www.lume.ufrgs.br:10183/142315Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2018-10-26T12:45:43Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv Plantwide periodical disturbances isolation and elimination in a petrochemical unit
title Plantwide periodical disturbances isolation and elimination in a petrochemical unit
spellingShingle Plantwide periodical disturbances isolation and elimination in a petrochemical unit
Farenzena, Marcelo
Diagnóstico de falhas
Válvulas (Engenharia)
Análise espectral
Fault diagnosis
Plant-wide disturbance
Oscillation
Independent Component Analysis
title_short Plantwide periodical disturbances isolation and elimination in a petrochemical unit
title_full Plantwide periodical disturbances isolation and elimination in a petrochemical unit
title_fullStr Plantwide periodical disturbances isolation and elimination in a petrochemical unit
title_full_unstemmed Plantwide periodical disturbances isolation and elimination in a petrochemical unit
title_sort Plantwide periodical disturbances isolation and elimination in a petrochemical unit
author Farenzena, Marcelo
author_facet Farenzena, Marcelo
Kayser, Cristine Alessandra
Trierweiler, Jorge Otávio
author_role author
author2 Kayser, Cristine Alessandra
Trierweiler, Jorge Otávio
author2_role author
author
dc.contributor.author.fl_str_mv Farenzena, Marcelo
Kayser, Cristine Alessandra
Trierweiler, Jorge Otávio
dc.subject.por.fl_str_mv Diagnóstico de falhas
Válvulas (Engenharia)
Análise espectral
topic Diagnóstico de falhas
Válvulas (Engenharia)
Análise espectral
Fault diagnosis
Plant-wide disturbance
Oscillation
Independent Component Analysis
dc.subject.eng.fl_str_mv Fault diagnosis
Plant-wide disturbance
Oscillation
Independent Component Analysis
description Reducing process variability is crucial to reach a more profitable operating point. Periodical disturbances, however, impose barriers to achieve this goal. Their effect can be strong since one disturbance that appears in a specific loop of a highly coupled plant can be seen in several loops. Thus, isolating their source and diagnosing their cause are essential. In this work, we describe the application of spectral independent component analysis to isolate a periodical disturbance that has a strong impact on the final variability in a polyethylene plant located in Southern Brazil. After the first analysis, the source was detected and the cause identified: valve stiction. To identify the cause (valve, bad tuning, or periodic disturbance), we used the methodology based on higher-order statistics. Once the valve problem had been overcome, the product variance was reduced by 93%.
publishDate 2015
dc.date.issued.fl_str_mv 2015
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dc.language.iso.fl_str_mv por
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dc.relation.ispartof.pt_BR.fl_str_mv Brazilian journal of chemical engineering. São Paulo, SP. Vol. 32, no. 4 (Oct./Dec. 2015), p. 919-927
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