Prediction of weld porosity (pit) in gas metal arc welds
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Shin, Seungmin | - |
dc.contributor.author | Kim, Min Seok | - |
dc.contributor.author | Rhee, Sehun | - |
dc.date.accessioned | 2021-08-02T11:26:00Z | - |
dc.date.available | 2021-08-02T11:26:00Z | - |
dc.date.created | 2021-05-11 | - |
dc.date.issued | 2019-09 | - |
dc.identifier.issn | 0268-3768 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/13206 | - |
dc.description.abstract | Recently, in the automobile industry, the use of zinc-plated high-strength steels has been increasing to lighten vehicles and improve safety. In this scenario, gas metal arc welding (GMAW) processes are applied to automobile bodies and chassis parts. However, porosity defects occur in the welds because of the zinc vapor formed in the zinc coating layer during the GMAW process. This causes a decrease in the strength of the welded portion. These porosity defects have internal porosity and external pits, but in the actual production line, the quality of the welds is assessed by the occurrence of defects in external pits. In this study, using arc voltage and a system based on the waveform of the welding current, feature variables were extracted to characterize the sizes of external pits formed in high tensile strength galvanized steel during the GMAW process. Subsequently, a size prediction model was applied to predict the sizes of the external defects in the pits, and the results were verified using a multiple linear regression model and an artificial neural network. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER LONDON LTD | - |
dc.title | Prediction of weld porosity (pit) in gas metal arc welds | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Rhee, Sehun | - |
dc.identifier.doi | 10.1007/s00170-019-03853-5 | - |
dc.identifier.scopusid | 2-s2.0-85068065351 | - |
dc.identifier.wosid | 000483808200072 | - |
dc.identifier.bibliographicCitation | INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, v.104, no.1-4, pp.1109 - 1120 | - |
dc.relation.isPartOf | INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | - |
dc.citation.title | INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | - |
dc.citation.volume | 104 | - |
dc.citation.number | 1-4 | - |
dc.citation.startPage | 1109 | - |
dc.citation.endPage | 1120 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Automation & Control Systems | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Automation & Control Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Manufacturing | - |
dc.subject.keywordPlus | Accident prevention | - |
dc.subject.keywordPlus | Automobile bodies | - |
dc.subject.keywordPlus | Automobile manufacture | - |
dc.subject.keywordPlus | Automotive industry | - |
dc.subject.keywordPlus | Defects | - |
dc.subject.keywordPlus | Forecasting | - |
dc.subject.keywordPlus | Galvanizing | - |
dc.subject.keywordPlus | Gas welding | - |
dc.subject.keywordPlus | High strength steel | - |
dc.subject.keywordPlus | Linear regression | - |
dc.subject.keywordPlus | Neural networks | - |
dc.subject.keywordPlus | Porosity | - |
dc.subject.keywordPlus | Tensile strength | - |
dc.subject.keywordPlus | Welds | - |
dc.subject.keywordPlus | Zinc coatings | - |
dc.subject.keywordPlus | Feature variable | - |
dc.subject.keywordPlus | Galvanized steels | - |
dc.subject.keywordPlus | Gas metal arc welding (GMAW) | - |
dc.subject.keywordPlus | High-tensile strength | - |
dc.subject.keywordPlus | Internal porosity | - |
dc.subject.keywordPlus | Multiple linear regression models | - |
dc.subject.keywordPlus | Pits | - |
dc.subject.keywordPlus | Size predictions | - |
dc.subject.keywordPlus | Gas metal arc welding | - |
dc.subject.keywordAuthor | GMAW | - |
dc.subject.keywordAuthor | High-strength steel | - |
dc.subject.keywordAuthor | Pits | - |
dc.subject.keywordAuthor | Feature variables | - |
dc.subject.keywordAuthor | Multiple linear regression model | - |
dc.subject.keywordAuthor | Artificial neural network | - |
dc.identifier.url | https://link.springer.com/article/10.1007/s00170-019-03853-5 | - |
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