High-precision laser focus positioning of rough surfaces by deep learning

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buir.contributor.authorElahi, Sepehr
buir.contributor.orcidElahi, Sepehr|0000-0001-5494-6465
dc.citation.epage107646-8en_US
dc.citation.issueNumber107646
dc.citation.spage107646-1
dc.citation.volumeNumber168
dc.contributor.authorPolat, Can
dc.contributor.authorYapici, Gizem Nuran
dc.contributor.authorElahi, Sepehr
dc.contributor.authorElahi, Parviz
dc.date.accessioned2024-03-27T08:12:14Z
dc.date.available2024-03-27T08:12:14Z
dc.date.issued2023-05-18
dc.departmentDepartment of Electrical and Electronics Engineering
dc.description.abstractThis work presents a precise positioning detection based on a convolutional neural network (CNN) to control the laser focus in laser material processing systems. The images of the diffraction patterns measured at different positions of the laser focus concerning the workpiece are classified in the range of the Rayleigh length of the focusing lens with an increment of about 7% of it. The experiment was carried out on different materials with different levels of surface roughness, such as copper, silicon, and steel, and over 99% accuracy in the positioning detection was achieved. Considering surface roughness and camera noise, a theoretical model is established, and the effects of these parameters on the accuracy of focus detection are also presented. The proposed method exhibits a noise-robust focus detection system and the potential for many precise positioning detection systems in industry and biology. © 2023 Elsevier Ltd.
dc.description.provenanceMade available in DSpace on 2024-03-27T08:12:14Z (GMT). No. of bitstreams: 1 High-precision_laser_focus_positioning_of_rough_surfaces_by_deep_learning.pdf: 2794207 bytes, checksum: 30ad7dd0ebc0f4048fe1f3aef6b6ec1f (MD5) Previous issue date: 2023-09en
dc.embargo.release2025-05-18
dc.identifier.doi10.1016/j.optlaseng.2023.107646
dc.identifier.eissn1873-0302
dc.identifier.issn0143-8166
dc.identifier.urihttps://hdl.handle.net/11693/115124
dc.language.isoen
dc.publisherElsevier Ltd
dc.relation.isversionofhttps://doi.org/10.1016/j.optlaseng.2023.107646
dc.rightsCC BY 4.0 DEED (Attribution 4.0 International)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.source.titleOptics and Lasers in Engineering
dc.subjectDeep learning
dc.subjectFocus detection
dc.subjectFourier optics
dc.subjectMachine learning
dc.subjectUltra-fast laser micromachining
dc.titleHigh-precision laser focus positioning of rough surfaces by deep learning
dc.typeArticle

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