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dc.contributor.authorPicon, Artzai
dc.contributor.authorVicente Rojo, Asier
dc.contributor.authorRodriguez-Vaamonde, Sergio
dc.contributor.authorArmentia, Jorge
dc.contributor.authorArteche, Jose Antonio
dc.contributor.authorMacaya, Inaki
dc.date.accessioned2017-11-23T15:57:26Z
dc.date.available2017-11-23T15:57:26Z
dc.date.issued2017-11-13
dc.identifier.issn1551-3203en
dc.identifier.urihttp://hdl.handle.net/11556/465
dc.description.abstractIn steelmaking process, close control of slag evolution is as important as control of steel composition. However, there are no industrially consolidated techniques that allow in-situ analysis of the slag chemical composition, as in the case of steel with OES-spectrometers. In this work, a method to analyze spectral reflectance of ladle furnace slag samples to estimate their composition is proposed. This method does not require sample preprocessing and is based on a regression algorithm that mathematically maps the spectral reflectance of the slag with its actual composition with errors lower than 10%. Specifically designed normalization and calibration steps have been proposed to allow a global model training with data from different locations. This allows real-time monitoring of the thermodynamical state of the steel process by feeding a thermodynamic equilibrium optimization model. The system has been validated on several ArcelorMittal locations achieving process savings of 0.71 Euro per liquid steel tons.en
dc.description.sponsorshipPartial financial support of this work by the Basque Government (Etorgai NUPROSS ER-2010/00001 and DAVOS ER-2014/0004 Projects) is gratefully acknowledged.en
dc.language.isoengen
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USAen
dc.titleLadle furnace slag characterization through hyperspectral reflectance regression model for secondary metallurgy process optimizationen
dc.typearticleen
dc.identifier.doi10.1109/tii.2017.2773068en
dc.isiYesen
dc.rights.accessRightsembargoedAccessen
dc.subject.keywordsHyper-spectral image processingen
dc.subject.keywordsSlag characterizationen
dc.subject.keywordsLadle furnaceen
dc.subject.keywordsSteel castingen
dc.subject.keywordsSecondary metallurgy process optimizationen
dc.identifier.essn1941-0050en
dc.issue.number99en
dc.journal.titleIEEE Transactions on Industrial Informaticsen
dc.page.final1en
dc.page.initial1en


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