Discontinuity detection in the shield metal arc welding process.
dc.contributor.author | Cocota Júnior, José Alberto Naves | |
dc.contributor.author | Garcia, Gabriel Carvalho | |
dc.contributor.author | Costa, Adilson Rodrigues da | |
dc.contributor.author | Lima, Milton Sérgio Fernandes de | |
dc.contributor.author | Rocha, Filipe Augusto Santos | |
dc.contributor.author | Freitas, Gustavo Medeiros | |
dc.date.accessioned | 2017-11-08T14:22:51Z | |
dc.date.available | 2017-11-08T14:22:51Z | |
dc.date.issued | 2017 | |
dc.description.abstract | This work proposes a new methodology for the detection of discontinuities in the weld bead applied in Shielded Metal ArcWelding (SMAW) processes. The detection system is based on two sensors—a microphone and piezoelectric—that acquire acoustic emissions generated during the welding. The feature vectors extracted from the sensor dataset are used to construct classifier models. The approaches based on Artificial Neural Network (ANN) and Support Vector Machine (SVM) classifiers are able to identify with a high accuracy the three proposed weld bead classes: desirable weld bead, shrinkage cavity and burn through discontinuities. Experimental results illustrate the system’s high accuracy, greater than 90% for each class. A novel Hierarchical Support Vector Machine (HSVM) structure is proposed to make feasible the use of this system in industrial environments. This approach presented 96.6% overall accuracy. Given the simplicity of the equipment involved, this system can be applied in the metal transformation industries. | pt_BR |
dc.identifier.citation | COCOTA JÚNIOR, J. A. N. et al. Discontinuity detection in the shield metal arc welding process. Sensors, v. 17, p. 1082, 2017. Disponível em: <http://www.mdpi.com/1424-8220/17/5/1082>. Acesso em: 29 set. 2017. | pt_BR |
dc.identifier.doi | https://doi.org/10.3390/s17051082 | |
dc.identifier.issn | 1424-8220 | |
dc.identifier.uri | http://www.repositorio.ufop.br/handle/123456789/9117 | |
dc.language.iso | en_US | pt_BR |
dc.rights | aberto | pt_BR |
dc.rights.license | This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Fonte: o próprio artigo. | pt_BR |
dc.subject | Support vector machine | pt_BR |
dc.subject | Artificial neural network | pt_BR |
dc.subject | Shielded metal arc welding | pt_BR |
dc.title | Discontinuity detection in the shield metal arc welding process. | pt_BR |
Arquivos
Pacote Original
1 - 1 de 1
Nenhuma Miniatura disponível
- Nome:
- ARTIGO_DiscontinuityDetectionShield.pdf
- Tamanho:
- 5.93 MB
- Formato:
- Adobe Portable Document Format
Licença do Pacote
1 - 1 de 1
Nenhuma Miniatura disponível
- Nome:
- license.txt
- Tamanho:
- 924 B
- Formato:
- Item-specific license agreed upon to submission
- Descrição: