DAMAGE IDENTIFICATION THROUGH THE USE OF HIGHORDER STATISTICS
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Interdisciplinar de Pesquisa em Engenharia |
Texto Completo: | https://periodicos.unb.br/index.php/ripe/article/view/20840 |
Resumo: | Structural Health Monitoring is based on the development of reliable and robust indicators capable to detect, locate, quantify and predict damage. Studies related to damage detection in civil engineering structures have a noticeable interest for researchers in this area. Indeed, the detection of structural changes likely to become critical can avoid the occurrence of major dysfunctions associated with social, economic and environmental consequences. Recently, many researchers have focused on dynamic assessment as part of structural diagnosis. Most of the studied techniques are based on time or frequency domain analyses to extract compressed information from modal characteristics or based on indicators built from these parameters. This work has as its main interest the use of highorder statistics (HOS) coupled with clustering techniques i.e. the k-means algorithm to detect structural modification (damage). The approach is applied directly to dynamic measurements (accelerations) obtained on site. In order to attest the efficiency of the proposed methodology,two investigations are carried out: a numerical model of a simply supported beam and a real case railway bridge, in France. It is shown that HOS coupled with clustering methods is able to distinguish structural conditions with adequate rates. |
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Revista Interdisciplinar de Pesquisa em Engenharia |
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DAMAGE IDENTIFICATION THROUGH THE USE OF HIGHORDER STATISTICSDamage detection. High-Order Statistics. Clustering methods. Raw.Structural Health Monitoring is based on the development of reliable and robust indicators capable to detect, locate, quantify and predict damage. Studies related to damage detection in civil engineering structures have a noticeable interest for researchers in this area. Indeed, the detection of structural changes likely to become critical can avoid the occurrence of major dysfunctions associated with social, economic and environmental consequences. Recently, many researchers have focused on dynamic assessment as part of structural diagnosis. Most of the studied techniques are based on time or frequency domain analyses to extract compressed information from modal characteristics or based on indicators built from these parameters. This work has as its main interest the use of highorder statistics (HOS) coupled with clustering techniques i.e. the k-means algorithm to detect structural modification (damage). The approach is applied directly to dynamic measurements (accelerations) obtained on site. In order to attest the efficiency of the proposed methodology,two investigations are carried out: a numerical model of a simply supported beam and a real case railway bridge, in France. It is shown that HOS coupled with clustering methods is able to distinguish structural conditions with adequate rates.Programa de Pós-Graduação em Integridade de Materiais da Engenharia2017-02-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.unb.br/index.php/ripe/article/view/2084010.26512/ripe.v2i25.20840Revista Interdisciplinar de Pesquisa em Engenharia; Vol. 2 No. 25 (2016): UNDERGRADUATE POSTER SESSION (I); 20-28Revista Interdisciplinar de Pesquisa em Engenharia; v. 2 n. 25 (2016): UNDERGRADUATE POSTER SESSION (I); 20-282447-6102reponame:Revista Interdisciplinar de Pesquisa em Engenhariainstname:Universidade de Brasília (UnB)instacron:UNBenghttps://periodicos.unb.br/index.php/ripe/article/view/20840/19211Copyright (c) 2018 Revista Interdisciplinar de Pesquisa em Engenharia - RIPEinfo:eu-repo/semantics/openAccessTorres, AlanCury, Alexandre2019-06-18T14:46:52Zoai:ojs.pkp.sfu.ca:article/20840Revistahttps://periodicos.unb.br/index.php/ripePUBhttps://periodicos.unb.br/index.php/ripe/oaianflor@unb.br2447-61022447-6102opendoar:2019-06-18T14:46:52Revista Interdisciplinar de Pesquisa em Engenharia - Universidade de Brasília (UnB)false |
dc.title.none.fl_str_mv |
DAMAGE IDENTIFICATION THROUGH THE USE OF HIGHORDER STATISTICS |
title |
DAMAGE IDENTIFICATION THROUGH THE USE OF HIGHORDER STATISTICS |
spellingShingle |
DAMAGE IDENTIFICATION THROUGH THE USE OF HIGHORDER STATISTICS Torres, Alan Damage detection. High-Order Statistics. Clustering methods. Raw. |
title_short |
DAMAGE IDENTIFICATION THROUGH THE USE OF HIGHORDER STATISTICS |
title_full |
DAMAGE IDENTIFICATION THROUGH THE USE OF HIGHORDER STATISTICS |
title_fullStr |
DAMAGE IDENTIFICATION THROUGH THE USE OF HIGHORDER STATISTICS |
title_full_unstemmed |
DAMAGE IDENTIFICATION THROUGH THE USE OF HIGHORDER STATISTICS |
title_sort |
DAMAGE IDENTIFICATION THROUGH THE USE OF HIGHORDER STATISTICS |
author |
Torres, Alan |
author_facet |
Torres, Alan Cury, Alexandre |
author_role |
author |
author2 |
Cury, Alexandre |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Torres, Alan Cury, Alexandre |
dc.subject.por.fl_str_mv |
Damage detection. High-Order Statistics. Clustering methods. Raw. |
topic |
Damage detection. High-Order Statistics. Clustering methods. Raw. |
description |
Structural Health Monitoring is based on the development of reliable and robust indicators capable to detect, locate, quantify and predict damage. Studies related to damage detection in civil engineering structures have a noticeable interest for researchers in this area. Indeed, the detection of structural changes likely to become critical can avoid the occurrence of major dysfunctions associated with social, economic and environmental consequences. Recently, many researchers have focused on dynamic assessment as part of structural diagnosis. Most of the studied techniques are based on time or frequency domain analyses to extract compressed information from modal characteristics or based on indicators built from these parameters. This work has as its main interest the use of highorder statistics (HOS) coupled with clustering techniques i.e. the k-means algorithm to detect structural modification (damage). The approach is applied directly to dynamic measurements (accelerations) obtained on site. In order to attest the efficiency of the proposed methodology,two investigations are carried out: a numerical model of a simply supported beam and a real case railway bridge, in France. It is shown that HOS coupled with clustering methods is able to distinguish structural conditions with adequate rates. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-02-10 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://periodicos.unb.br/index.php/ripe/article/view/20840 10.26512/ripe.v2i25.20840 |
url |
https://periodicos.unb.br/index.php/ripe/article/view/20840 |
identifier_str_mv |
10.26512/ripe.v2i25.20840 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://periodicos.unb.br/index.php/ripe/article/view/20840/19211 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2018 Revista Interdisciplinar de Pesquisa em Engenharia - RIPE info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2018 Revista Interdisciplinar de Pesquisa em Engenharia - RIPE |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Programa de Pós-Graduação em Integridade de Materiais da Engenharia |
publisher.none.fl_str_mv |
Programa de Pós-Graduação em Integridade de Materiais da Engenharia |
dc.source.none.fl_str_mv |
Revista Interdisciplinar de Pesquisa em Engenharia; Vol. 2 No. 25 (2016): UNDERGRADUATE POSTER SESSION (I); 20-28 Revista Interdisciplinar de Pesquisa em Engenharia; v. 2 n. 25 (2016): UNDERGRADUATE POSTER SESSION (I); 20-28 2447-6102 reponame:Revista Interdisciplinar de Pesquisa em Engenharia instname:Universidade de Brasília (UnB) instacron:UNB |
instname_str |
Universidade de Brasília (UnB) |
instacron_str |
UNB |
institution |
UNB |
reponame_str |
Revista Interdisciplinar de Pesquisa em Engenharia |
collection |
Revista Interdisciplinar de Pesquisa em Engenharia |
repository.name.fl_str_mv |
Revista Interdisciplinar de Pesquisa em Engenharia - Universidade de Brasília (UnB) |
repository.mail.fl_str_mv |
anflor@unb.br |
_version_ |
1798315224340627456 |