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  4. Acoustic Process Monitoring in Laser Beam Welding
 
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2020
Journal Article
Titel

Acoustic Process Monitoring in Laser Beam Welding

Abstract
Structure-borne acoustic emission (AE) measurement shows major advantages regarding quality assurance and process control in industrial applications. In this paper, laser beam welding of steel and aluminum was carried out under varying process parameters (welding speed, focal position) in order to provide data by means of structure-borne AE and simultaneously high-speed video recordings. The analysis is based on conventionally (e.g. filtering, autocorrelation, spectrograms) as well as machine learning methods (convolutional neural nets) and showed promising results with respect to the use of structure-borne AE for process monitoring using the example of spatter formation.
Author(s)
Schmidt, Leander
Technische Universität Ilmenau, Production Technology Group, Ilmenau, Germany
Römer, Florian
Fraunhofer-Institut für Zerstörungsfreie Prüfverfahren IZFP
Böttger, David
Fraunhofer-Institut für Zerstörungsfreie Prüfverfahren IZFP
Leinenbach, Frank
Fraunhofer-Institut für Zerstörungsfreie Prüfverfahren IZFP
Straß, Benjamin
Fraunhofer-Institut für Zerstörungsfreie Prüfverfahren IZFP
Wolter, Bernd
Fraunhofer-Institut für Zerstörungsfreie Prüfverfahren IZFP
Stricker, Klaus
Technische Universität Ilmenau, Production Technology Group, Ilmenau, Germany
Seibold, Marc
Technische Universität Ilmenau, Production Technology Group, Ilmenau, Germany
Bergmann, Jean Pierre
Technische Universität Ilmenau, Production Technology Group, Ilmenau, Germany
Galdo, Giovanni del
Fraunhofer-Institut für Integrierte Schaltungen IIS
Zeitschrift
Procedia CIRP
Project(s)
ATTRACT
Funder
Fraunhofer-Gesellschaft FhG
Konferenz
Conference on Photonic Technologies (LANE) 2020
DOI
10.1016/j.procir.2020.09.139
File(s)
N-606129.pdf (1.6 MB)
Language
English
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Fraunhofer-Institut für Integrierte Schaltungen IIS
Fraunhofer-Institut für Zerstörungsfreie Prüfverfahren IZFP
Tags
  • structure-borne acous...

  • process monitoring

  • machine learning

  • laser beam welding

  • melt pool dynamic

  • seam imperfections

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