Show simple item record

dc.contributor.authorHartung, Julia
dc.date.accessioned2024-03-18T13:31:49Z
dc.date.available2024-03-18T13:31:49Z
dc.date.issued2024
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/88624
dc.description.abstractThe increasing use of automated laser welding processes causes high demands on process monitoring. This work demonstrates methods that use a camera mounted on the focussing optics to perform pre-, in-, and post-process monitoring of welding processes. The implementation uses machine learning methods. All algorithms consider the integration into industrial processes. These challenges include a small database, limited industrial manufacturing inference hardware, and user acceptance.en_US
dc.languageEnglishen_US
dc.relation.ispartofseriesForschungsberichte aus der Industriellen Informationstechniken_US
dc.subject.classificationthema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineeringen_US
dc.subject.otherCNN; stacked dilated U-Net; semantic segmentation; hairpin technology; laser welding; quality assurance; machine learning; Qualitätssicherung; semantische Segmentierung; Hairpin Technologie; Laserschweißen; Maschinelles Lernen; Künstliche Intelligenzen_US
dc.titleMachine Learning for Camera-Based Monitoring of Laser Welding Processesen_US
dc.typebook
oapen.identifier.doi10.5445/KSP/1000164716en_US
oapen.relation.isPublishedBy44e29711-8d53-496b-85cc-3d10c9469be9en_US
oapen.series.number32en_US
oapen.pages258en_US
peerreview.anonymityAll identities known
peerreview.id51a542ec-eaeb-47c2-861d-6022e981a97a
peerreview.open.reviewNo
peerreview.publish.responsibilityBooks or series editor
peerreview.review.stagePre-publication
peerreview.review.typeFull text
peerreview.reviewer.typeEditorial board member
peerreview.reviewer.typeExternal peer reviewer
peerreview.titleDissertations in Series (Dissertationen in Schriftenreihe)


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record