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@ARTICLE{Brueggenjuergen:622958,
      author       = {Brueggenjuergen, Jan and Spurk, Christoph and Hummel, Marc
                      and Franz, Christoph and Häusler, Andrè and Olowinsky,
                      Alexander and Beckmann, Felix and Moosmann, Julian},
      title        = {{A}nalyzing multispectral emission and synchrotron data to
                      evaluate the quality of laser welds on copper},
      journal      = {Journal of laser applications},
      volume       = {36},
      number       = {3},
      issn         = {1042-346X},
      address      = {Orlando, Fla.},
      publisher    = {Laser Inst. of America},
      reportid     = {PUBDB-2025-00594},
      pages        = {032032},
      year         = {2024},
      abstract     = {The validation of laser welding of metallic materials is
                      challenging due to its highly dynamic processes and limited
                      accessibility to the weld. The measurement of process
                      emissions and the processing laser beam are one way to
                      record highly dynamic process phenomena. However, these
                      recordings always take place via the surface of the weld.
                      Phenomena on the inside are only implicitly recognizable in
                      the data and require further processing. To increase the
                      validity of the diagnostic process, the multispectral
                      emission data are synchronized with synchrotron data
                      consisting of in situ high-speed images based on phase
                      contrast videography. The welding process is
                      transilluminated by synchrotron radiation and recorded
                      during execution, providing clear contrasts between solid,
                      liquid, and gaseous material phases. Thus, dynamics of the
                      vapor capillary and the formation of defects such as pores
                      can be recorded with high spatial and temporal resolution of
                      <5 μm and >5 kHz. In this paper, laser welding of
                      copper Cu-ETP and CuSn6 is investigated at the Deutsches
                      Elektronen-Synchrotron (DESY). The synchronization is
                      achieved by leveraging a three-stage deep learning approach.
                      A preprocessing Mask-R-CNN, dimensionality reduction
                      PCA/Autoencoders, and a final LSTM/Transformer stage provide
                      end-to-end defect detection capabilities. Integrated
                      gradients allow for the extraction of correlations between
                      defects and emission data. The novel approach of correlating
                      image and sensor data increases the informative value of the
                      sensor data. It aims to characterize welds based on the
                      sensor data not only according to IO/NIO but also to provide
                      a quantitative description of the defects in the weld.},
      cin          = {DOOR ; HAS-User / Hereon},
      ddc          = {530},
      cid          = {I:(DE-H253)HAS-User-20120731 / I:(DE-H253)Hereon-20210428},
      pnm          = {6G3 - PETRA III (DESY) (POF4-6G3) / DFG project
                      G:(GEPRIS)236616214 - SFB 1120: Bauteilpräzision durch
                      Beherrschung von Schmelze und Erstarrung in
                      Produktionsprozessen (236616214) / FS-Proposal: BAG-20211050
                      (BAG-20211050)},
      pid          = {G:(DE-HGF)POF4-6G3 / G:(GEPRIS)236616214 /
                      G:(DE-H253)BAG-20211050},
      experiment   = {EXP:(DE-H253)P-P07-20150101},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001298503700001},
      doi          = {10.2351/7.0001600},
      url          = {https://bib-pubdb1.desy.de/record/622958},
}