High accuracy beam splitting using spatial light modulator combined with machine learning algorithms

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Dmitriy Mikhaylov - , Chair of Laser-based Manufacturing, Robert Bosch GmbH (Author)
  • Baifan Zhou - , Robert Bosch GmbH, Karlsruhe Institute of Technology (Author)
  • Thomas Kiedrowski - , Robert Bosch GmbH (Author)
  • Ralf Mikut - , Karlsruhe Institute of Technology (Author)
  • Andrés Fabián Lasagni - , Chair of Laser-based Manufacturing, Fraunhofer Institute for Material and Beam Technology (Author)

Abstract

Phase-only spatial light modulators are ideal for the generation of beam splitter profiles to parallelize a variety of laser processes. A novel approach for the calculation of phase holograms is proposed to achieve a highly accurate power distribution over all spots. The Iterative Fourier Transform Algorithm (IFTA) is extended by the use of different machine learning methods, which are trained in an open camera-feedback loop. After the training phase, improvement of the beam splitting accuracy is then validated experimentally. The advantage of the presented approach is shown by comparing it to the standard IFTA algorithm. Finally, use of the approach is demonstrated through metal marking with an ultrashort pulse laser.

Details

Original languageEnglish
Pages (from-to)227-235
Number of pages9
JournalOptics and lasers in engineering
Volume121
Publication statusPublished - Oct 2019
Peer-reviewedYes

Keywords

Keywords

  • Beam splitting, Convolutional neural networks, Laser material processing, Machine learning, Spatial light modulator