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Automatic visual inspection system for solder paste deposition in PCBs

datacite.subject.fosCiências Naturais::Ciências da Computação e da Informação
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg10:Reduzir as Desigualdades
datacite.subject.sdg11:Cidades e Comunidades Sustentáveis
dc.contributor.authorPaulo, Guilherme B. F.
dc.contributor.authorPerdigoto, Luís M. R.
dc.contributor.authorFaria, Sergio M. M.
dc.date.accessioned2026-03-27T18:07:08Z
dc.date.available2026-03-27T18:07:08Z
dc.date.issued2021-02
dc.descriptionPaulo, Guilherme B.F. - Scopus ID: 57224527170
dc.descriptionEISBN - 978-1-6654-1588-0
dc.descriptionDate of Conference: 11-12 February 2021
dc.description.abstractThe growth of the electronics industry led to a need for efficient methods of testing and validation of printed circuit boards (PCB). It is necessary to identify defects that might appear in a component in early production stages. This task may be performed by automatic inspection systems, showing advantages in speed, accuracy and repeatability, over human inspection. This paper describes a visual inspection system that is able to detect solder paste deposition defects on a PCB. The PCB image is analysed to segment the areas with solder paste and then, by comparing with reference data from the PCB design files, defects are identified, either because of missing or excess solder. The system is based on low cost components, namely a Raspberry Pi Compute Module and two Raspberry Pi v2 cameras. Experimental tests performed with the prototype, regarding the PCB defect detection and execution time, allowed to conclude the system can aid human visual inspection in a production line.eng
dc.description.sponsorshipThis work was partially supported by the FCT/MCTES through national funds and when applicable co-funded by EU funds under the project UIDB/EEA/50008/2020, and DigiWest - Wireless and Embedded Solutions, Lda, Leiria, Portugal (SIFIDE-I3D-SCE).
dc.identifier.citationG. B. F. Paulo, L. M. R. Perdigoto and S. M. M. Faria, "Automatic visual inspection system for solder paste deposition in PCBs," 2021 Telecoms Conference (ConfTELE), Leiria, Portugal, 2021, pp. 1-6, doi: https://doi.org/10.1109/ConfTELE50222.2021.9435522.
dc.identifier.doi10.1109/conftele50222.2021.9435522
dc.identifier.isbn978-1-6654-4680-8
dc.identifier.isbn978-1-6654-1588-0
dc.identifier.urihttp://hdl.handle.net/10400.8/16040
dc.language.isoeng
dc.peerreviewedyes
dc.publisherIEEE Canada
dc.relation.hasversionhttps://ieeexplore.ieee.org/document/9435522
dc.relation.ispartof2021 Telecoms Conference (ConfTELE)
dc.rights.uriN/A
dc.subjectVisual inspection
dc.subjectPCB inspection
dc.subjectImage processing
dc.subjectSolder paste
dc.titleAutomatic visual inspection system for solder paste deposition in PCBseng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2021-02
oaire.citation.conferencePlaceLeiria, Portugal
oaire.citation.title2021 Telecoms Conference, ConfTELE 2021
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNamePerdigoto
person.familyNameFaria
person.givenNameLuis
person.givenNameSergio
person.identifier.ciencia-id8815-4101-28DD
person.identifier.orcid0000-0002-2626-3154
person.identifier.orcid0000-0002-0993-9124
person.identifier.ridC-5245-2011
person.identifier.scopus-author-id14027853900
relation.isAuthorOfPublication21974cb3-96e9-4071-bbd1-149f86160821
relation.isAuthorOfPublicationf69bd4d6-a6ef-4d20-8148-575478909661
relation.isAuthorOfPublication.latestForDiscovery21974cb3-96e9-4071-bbd1-149f86160821

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The growth of the electronics industry led to a need for efficient methods of testing and validation of printed circuit boards (PCB). It is necessary to identify defects that might appear in a component in early production stages. This task may be performed by automatic inspection systems, showing advantages in speed, accuracy and repeatability, over human inspection. This paper describes a visual inspection system that is able to detect solder paste deposition defects on a PCB. The PCB image is analysed to segment the areas with solder paste and then, by comparing with reference data from the PCB design files, defects are identified, either because of missing or excess solder. The system is based on low cost components, namely a Raspberry Pi Compute Module and two Raspberry Pi v2 cameras. Experimental tests performed with the prototype, regarding the PCB defect detection and execution time, allowed to conclude the system can aid human visual inspection in a production line.
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