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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21d.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34T/45AQ32L
Repositorysid.inpe.br/mtc-m21d/2021/08.24.12.30   (restricted access)
Last Update2021:08.24.12.30.16 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21d/2021/08.24.12.30.16
Metadata Last Update2022:04.03.23.14.03 (UTC) administrator
DOI10.1155/2021/9998187
ISSN1687-725X
Citation KeyFariasSaotCampShig:2021:DaDeMe
TitleA Damage Detection Method Using Neural Network Optimized by Multiple Particle Collision Algorithm
Year2021
Access Date2024, May 09
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size2647 KiB
2. Context
Author1 Farias, Sergio V.
2 Saotome, O.
3 Campos Velho, Haroldo Fraga de
4 Shiguemori, Elcio H.
Resume Identifier1
2
3 8JMKD3MGP5W/3C9JHC3
ORCID1 0000-0001-6753-9607
2 0000-0002-1568-9299
3 0000-0003-4968-5330
4 0000-0001-5226-0435
Group1
2
3 COPDT-CGIP-INPE-MCTI-GOV-BR
Affiliation1 Instituto Tecnológico de Aeronáutica (ITA)
2 Instituto Tecnológico de Aeronáutica (ITA)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
4 Instituto de Estudos Avançados (IEAv)
Author e-Mail Address1 sertone@gmail.com
2
3 haroldo.camposvelho@inpe.br
JournalJournal of Sensors
Volume2021
Pagese9998187
History (UTC)2021-11-05 11:51:53 :: simone -> administrator :: 2021
2022-04-03 23:14:03 :: administrator -> simone :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
AbstractA critical task of structural health monitoring is damage detection and localization. Lamb wave propagation methods have been successfully applied for damage identification in plate-like structures. However, Lamb wave processing is still a challenging task due to its multimodal and dispersive characteristics. To address this issue, data-driven machine learning approaches as artificial neural network (ANN) have been proposed. However, the effectiveness of ANN can be improved based on its architecture and the learning strategy employed to train it. The present paper proposes a Multiple Particle Collision Algorithm (MPCA) to design an optimum ANN architecture to detect and locate damages in plate-like structures. For the first time in the literature, the MPCA is applied to find damages in plate-like structures. The present work uses one piezoelectric transducer to generate Lamb wave signals on an aluminum plate structure and a linear array of four transducers to capture the scattered signals. The continuous wavelet transform (CWT) processes the captured signals to estimate the time-of-flight (ToF) that is the ANN inputs. The ANN output is the damage spatial coordinates. In addition to MPCA optimization, this paper uses a quantitative entropy-based criterion to find the best mother wavelet and the scale values. The presented experimental results show that MPCA is capable of finding a simple ANN architecture with good generalization performance in the proposed damage localization application. The proposed method is compared with the 1-dimensional convolutional neural network (1D-CNN). A discussion about the advantages and limitations of the proposed method is presented.
AreaCOMP
Arrangementurlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGIP > A Damage Detection...
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4. Conditions of access and use
Languageen
Target Filefarias_damage_2021.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/46KUES5
Citing Item Listsid.inpe.br/mtc-m21/2012/07.13.14.49.40 2
sid.inpe.br/bibdigital/2022/04.03.23.11 2
DisseminationWEBSCI; PORTALCAPES; SCOPUS.
Host Collectionurlib.net/www/2021/06.04.03.40
6. Notes
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