dc.contributor.author | Picon, Artzai | |
dc.contributor.author | Vicente Rojo, Asier | |
dc.contributor.author | Rodriguez-Vaamonde, Sergio | |
dc.contributor.author | Armentia, Jorge | |
dc.contributor.author | Arteche, Jose Antonio | |
dc.contributor.author | Macaya, Inaki | |
dc.date.accessioned | 2017-11-23T15:57:26Z | |
dc.date.available | 2017-11-23T15:57:26Z | |
dc.date.issued | 2017-11-13 | |
dc.identifier.issn | 1551-3203 | en |
dc.identifier.uri | http://hdl.handle.net/11556/465 | |
dc.description.abstract | In 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.sponsorship | Partial 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.iso | eng | en |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA | en |
dc.title | Ladle furnace slag characterization through hyperspectral reflectance regression model for secondary metallurgy process optimization | en |
dc.type | journal article | en |
dc.identifier.doi | 10.1109/tii.2017.2773068 | en |
dc.isi | Yes | en |
dc.rights.accessRights | embargoed access | en |
dc.subject.keywords | Hyper-spectral image processing | en |
dc.subject.keywords | Slag characterization | en |
dc.subject.keywords | Ladle furnace | en |
dc.subject.keywords | Steel casting | en |
dc.subject.keywords | Secondary metallurgy process optimization | en |
dc.identifier.essn | 1941-0050 | en |
dc.issue.number | 99 | en |
dc.journal.title | IEEE Transactions on Industrial Informatics | en |
dc.page.final | 1 | en |
dc.page.initial | 1 | en |