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EEMD-MUSIC-Based Analysis for Natural Frequencies Identification of Structures Using Artificial and Natural Excitations

This paper presents a new EEMD-MUSIC- (ensemble empirical mode decomposition-multiple signal classification-) based methodology to identify modal frequencies in structures ranging from free and ambient vibration signals produced by artificial and natural excitations and also considering several fact...

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Autores principales: Camarena-Martinez, David, Amezquita-Sanchez, Juan P., Valtierra-Rodriguez, Martin, Romero-Troncoso, Rene J., Osornio-Rios, Roque A., Garcia-Perez, Arturo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3934768/
https://www.ncbi.nlm.nih.gov/pubmed/24683346
http://dx.doi.org/10.1155/2014/587671
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author Camarena-Martinez, David
Amezquita-Sanchez, Juan P.
Valtierra-Rodriguez, Martin
Romero-Troncoso, Rene J.
Osornio-Rios, Roque A.
Garcia-Perez, Arturo
author_facet Camarena-Martinez, David
Amezquita-Sanchez, Juan P.
Valtierra-Rodriguez, Martin
Romero-Troncoso, Rene J.
Osornio-Rios, Roque A.
Garcia-Perez, Arturo
author_sort Camarena-Martinez, David
collection PubMed
description This paper presents a new EEMD-MUSIC- (ensemble empirical mode decomposition-multiple signal classification-) based methodology to identify modal frequencies in structures ranging from free and ambient vibration signals produced by artificial and natural excitations and also considering several factors as nonstationary effects, close modal frequencies, and noisy environments, which are common situations where several techniques reported in literature fail. The EEMD and MUSIC methods are used to decompose the vibration signal into a set of IMFs (intrinsic mode functions) and to identify the natural frequencies of a structure, respectively. The effectiveness of the proposed methodology has been validated and tested with synthetic signals and under real operating conditions. The experiments are focused on extracting the natural frequencies of a truss-type scaled structure and of a bridge used for both highway traffic and pedestrians. Results show the proposed methodology as a suitable solution for natural frequencies identification of structures from free and ambient vibration signals.
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spelling pubmed-39347682014-03-30 EEMD-MUSIC-Based Analysis for Natural Frequencies Identification of Structures Using Artificial and Natural Excitations Camarena-Martinez, David Amezquita-Sanchez, Juan P. Valtierra-Rodriguez, Martin Romero-Troncoso, Rene J. Osornio-Rios, Roque A. Garcia-Perez, Arturo ScientificWorldJournal Research Article This paper presents a new EEMD-MUSIC- (ensemble empirical mode decomposition-multiple signal classification-) based methodology to identify modal frequencies in structures ranging from free and ambient vibration signals produced by artificial and natural excitations and also considering several factors as nonstationary effects, close modal frequencies, and noisy environments, which are common situations where several techniques reported in literature fail. The EEMD and MUSIC methods are used to decompose the vibration signal into a set of IMFs (intrinsic mode functions) and to identify the natural frequencies of a structure, respectively. The effectiveness of the proposed methodology has been validated and tested with synthetic signals and under real operating conditions. The experiments are focused on extracting the natural frequencies of a truss-type scaled structure and of a bridge used for both highway traffic and pedestrians. Results show the proposed methodology as a suitable solution for natural frequencies identification of structures from free and ambient vibration signals. Hindawi Publishing Corporation 2014-02-10 /pmc/articles/PMC3934768/ /pubmed/24683346 http://dx.doi.org/10.1155/2014/587671 Text en Copyright © 2014 David Camarena-Martinez et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Camarena-Martinez, David
Amezquita-Sanchez, Juan P.
Valtierra-Rodriguez, Martin
Romero-Troncoso, Rene J.
Osornio-Rios, Roque A.
Garcia-Perez, Arturo
EEMD-MUSIC-Based Analysis for Natural Frequencies Identification of Structures Using Artificial and Natural Excitations
title EEMD-MUSIC-Based Analysis for Natural Frequencies Identification of Structures Using Artificial and Natural Excitations
title_full EEMD-MUSIC-Based Analysis for Natural Frequencies Identification of Structures Using Artificial and Natural Excitations
title_fullStr EEMD-MUSIC-Based Analysis for Natural Frequencies Identification of Structures Using Artificial and Natural Excitations
title_full_unstemmed EEMD-MUSIC-Based Analysis for Natural Frequencies Identification of Structures Using Artificial and Natural Excitations
title_short EEMD-MUSIC-Based Analysis for Natural Frequencies Identification of Structures Using Artificial and Natural Excitations
title_sort eemd-music-based analysis for natural frequencies identification of structures using artificial and natural excitations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3934768/
https://www.ncbi.nlm.nih.gov/pubmed/24683346
http://dx.doi.org/10.1155/2014/587671
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