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dc.contributor.authorRodriguez, Alvaro
dc.contributor.authorGonzalez, Carlos
dc.contributor.authorFernandez, Andres
dc.contributor.authorRodriguez, Francisco
dc.contributor.authorDelgado, Tamara
dc.contributor.authorBellmann, Martin Pawel
dc.date.accessioned2021-08-19T08:22:29Z
dc.date.available2021-08-19T08:22:29Z
dc.date.created2021-03-21T14:19:41Z
dc.date.issued2020
dc.identifier.citationJournal of Intelligent Manufacturing. 2020, 32 1163-1172.en_US
dc.identifier.issn0956-5515
dc.identifier.urihttps://hdl.handle.net/11250/2770216
dc.description.abstractSolar cells represent one of the most important sources of clean energy in modern societies. Solar cell manufacturing is a delicate process that often introduces defects that reduce cell efficiency or compromise durability. Current inspection systems detect and discard faulty cells, wasting a significant percentage of resources. We introduce Cell Doctor, a new inspection system that uses state of the art techniques to locate and classify defects in solar cells and performs a diagnostic and treatment process to isolate or eliminate the defects. Cell Doctor uses a fully automatic process that can be included in a manufacturing line. Incoming solar cells are first moved with a robotic arm to an Electroluminescence diagnostic station, where they are imaged and analysed with a set of Gabor filters, a Principal Component Analysis technique, a Random Forest classifier and different image processing techniques to detect possible defects in the surface of the cell. After the diagnosis, a laser station performs an isolation or cutting process depending on the detected defects. In a final stage, the solar cells are characterised in terms of their I–V Curve and I–V Parameters, in a Solar Simulator station. We validated and tested Cell Doctor with a labelled dataset of images of monocrystalline silicon cells, obtaining an accuracy and recall above 90% for Cracks, Area Defects and Finger interruptions; and precision values of 77% for Finger Interruptions and above 90% for Cracks and Area Defects. Which allows Cell Doctor to diagnose and repair solar cells in an industrial environment in a fully automatic way.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.subjectGabor filtersen_US
dc.subjectPCA en_US
dc.subjectRandom forest en_US
dc.subjectElectroluminescence imaging en_US
dc.subjectDefect classification en_US
dc.subjectAutomatic inspectionen_US
dc.subjectSolar cell manufacturing en_US
dc.subjectPhotovoltaics en_US
dc.titleAutomatic solar cell diagnosis and treatmenten_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© The Author(s) 2020en_US
dc.source.pagenumber1163-1172en_US
dc.source.volume32en_US
dc.source.journalJournal of Intelligent Manufacturingen_US
dc.identifier.doi10.1007/s10845-020-01642-6
dc.identifier.cristin1899675
dc.relation.projectEC/H2020/679692en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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