Dataset from healthy and defective spot welds in refill friction stir spot welding using acoustic emission
The dataset presented in this paper deals with real-time measurements carried out during the welding of 78 spot welds including heathy and defective states. These measurements are composed of acoustic emission signals and welding parameters. Acoustic emission signals were captured by three different...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-12-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340922009532 |
| _version_ | 1811206488817926144 |
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| author | Fethi Dahmene Slah Yaacoubi Mahjoub El Mountassir Gaëlle Porot Mohamed Masmoudi Pascal Nennig Uceu Fuad Hasan Suhuddin Jorge Fernandez dos Santos |
| author_facet | Fethi Dahmene Slah Yaacoubi Mahjoub El Mountassir Gaëlle Porot Mohamed Masmoudi Pascal Nennig Uceu Fuad Hasan Suhuddin Jorge Fernandez dos Santos |
| author_sort | Fethi Dahmene |
| collection | DOAJ |
| description | The dataset presented in this paper deals with real-time measurements carried out during the welding of 78 spot welds including heathy and defective states. These measurements are composed of acoustic emission signals and welding parameters. Acoustic emission signals were captured by three different piezoelectric sensors, which are connected to a Vallen AMSY5 system through preamplifiers. Welding parameters where digitized using the M-SCOPE software. Both measurements can be used for the establishment of an automatic criterion able to detect defective spot welds in Refill Friction Stir Spot Welding. |
| first_indexed | 2024-04-12T03:48:21Z |
| format | Article |
| id | doaj.art-27c2b2c8da26483fa3f527e835d17a07 |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-04-12T03:48:21Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-27c2b2c8da26483fa3f527e835d17a072022-12-22T03:49:03ZengElsevierData in Brief2352-34092022-12-0145108750Dataset from healthy and defective spot welds in refill friction stir spot welding using acoustic emissionFethi Dahmene0Slah Yaacoubi1Mahjoub El Mountassir2Gaëlle Porot3Mohamed Masmoudi4Pascal Nennig5Uceu Fuad Hasan Suhuddin6Jorge Fernandez dos Santos7Equipe Monitoring et Intelligence Artificielle, Institut de Soudure, 4 boulevard Henri Becquerel, Yutz 57970, France; Corresponding authors.Equipe Monitoring et Intelligence Artificielle, Institut de Soudure, 4 boulevard Henri Becquerel, Yutz 57970, France; Corresponding authors.Equipe Monitoring et Intelligence Artificielle, Institut de Soudure, 4 boulevard Henri Becquerel, Yutz 57970, FranceEquipe CND avancés, Institut de Soudure, 4 boulevard Henri Becquerel, Yutz 57970, FranceEquipe Monitoring et Intelligence Artificielle, Institut de Soudure, 4 boulevard Henri Becquerel, Yutz 57970, FranceEquipe CND avancés, Institut de Soudure, 4 boulevard Henri Becquerel, Yutz 57970, FranceMaterials Mechanics, Solid State Joining Processes, Helmholtz-Zentrum Hereon, Institute of Materials Research, Max-Planck-St.1, Geesthacht 21502, GermanyMaterials Mechanics, Solid State Joining Processes, Helmholtz-Zentrum Hereon, Institute of Materials Research, Max-Planck-St.1, Geesthacht 21502, GermanyThe dataset presented in this paper deals with real-time measurements carried out during the welding of 78 spot welds including heathy and defective states. These measurements are composed of acoustic emission signals and welding parameters. Acoustic emission signals were captured by three different piezoelectric sensors, which are connected to a Vallen AMSY5 system through preamplifiers. Welding parameters where digitized using the M-SCOPE software. Both measurements can be used for the establishment of an automatic criterion able to detect defective spot welds in Refill Friction Stir Spot Welding.http://www.sciencedirect.com/science/article/pii/S2352340922009532Refill friction stir spot weldingProcess monitoringCondition monitoringDefect detectionAcoustic emission |
| spellingShingle | Fethi Dahmene Slah Yaacoubi Mahjoub El Mountassir Gaëlle Porot Mohamed Masmoudi Pascal Nennig Uceu Fuad Hasan Suhuddin Jorge Fernandez dos Santos Dataset from healthy and defective spot welds in refill friction stir spot welding using acoustic emission Data in Brief Refill friction stir spot welding Process monitoring Condition monitoring Defect detection Acoustic emission |
| title | Dataset from healthy and defective spot welds in refill friction stir spot welding using acoustic emission |
| title_full | Dataset from healthy and defective spot welds in refill friction stir spot welding using acoustic emission |
| title_fullStr | Dataset from healthy and defective spot welds in refill friction stir spot welding using acoustic emission |
| title_full_unstemmed | Dataset from healthy and defective spot welds in refill friction stir spot welding using acoustic emission |
| title_short | Dataset from healthy and defective spot welds in refill friction stir spot welding using acoustic emission |
| title_sort | dataset from healthy and defective spot welds in refill friction stir spot welding using acoustic emission |
| topic | Refill friction stir spot welding Process monitoring Condition monitoring Defect detection Acoustic emission |
| url | http://www.sciencedirect.com/science/article/pii/S2352340922009532 |
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