Browsing by Author "Vicente, Asier"
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Item Ladle furnace slag characterization through hyperspectral reflectance regression model for secondary metallurgy process optimization(2017-11-13) Picon, Artzai; Vicente Rojo, Asier; Rodriguez-Vaamonde, Sergio; Armentia, Jorge; Arteche, Jose Antonio; Macaya, Inaki; Vicente, Asier; Tecnalia Research & Innovation; COMPUTER_VISION; INDUSTRY_THINGSIn 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.Item Magnetic field-based arc stability sensor for electric arc furnaces(2020-02) Vicente, Asier; Picon, Artzai; Arteche, Jose Antonio; Linares, Miguel; Velasco, Arturo; Sainz, Jose Angel; COMPUTER_VISIONDuring the last decades the strategy to define the optimal Electric Arc Furnaces (EAF) electrical operational parameters has been constantly evolving. Foaming slag practice is currently used to allow high power factors that ensures higher energy efficiency. However, this performance depends on strict electric arc stability control. Control strategies for these are normally defined for alternating current furnaces (AC EAF) and are based on intrusive and highly expensive systems. In this work we analyze the variation of the magnetic field vector around the direct current EAF (DC EAF) and its relationship with arc stability. We propose a cheap stability control system with no installation or integration requirements and thus, easily implementable to both AC and DC EAFs. To this end we have built a non-intrusive and low-cost 3-axis Hall-effect sensor that can be mounted neighboring the furnace’s electrical bars. The sensor allows acquiring the magnetic field magnitude and orientation that provides a newly defined arc stability factor metric. This proposed Arc Stability Index has been compared with three different alternative well established and more expensive measurement methodologies obtaining with similar results. The proposed index serves as a closed loop signal to the electrical regulation for controlling the arc voltage, ensuring the most convenient arc length that guaranties non-instabilities. The new system was developed and industrially validated at two different DC EAF’s in ArcelorMittal demonstrating an improvement of 6.7 kWh per Liquid steel ton during the evaluated period and a time reduction of 1.1 min per heat over the current standard procedure. Additional validation tests were also carried out also in ArcelorMittal AC EAF proving the capability of this technology for both AC and DC of furnaces.Item A Probabilistic Model and Capturing Device for Remote Simultaneous Estimation of Spectral Emissivity and Temperature of Hot Emissive Materials(2021) Picon, Artzai; Alvarez-Gila, Aitor; Arteche, Jose Antonio; Lopez, Gabriel A.; Vicente, Asier; Tecnalia Research & Innovation; COMPUTER_VISION; VISUALEstimating the temperature of hot emissive samples (e.g. liquid slag) in the context of harsh industrial environments such as steelmaking plants is a crucial yet challenging task, which is typically addressed by means of methods that require physical contact. Current remote methods require information on the emissivity of the sample. However, the spectral emissivity is dependent on the sample composition and temperature itself, and it is hardly measurable unless under controlled laboratory procedures. In this work, we present a portable device and associated probabilistic model that can simultaneously produce quasi real-time estimates for temperature and spectral emissivity of hot samples in the [0.2, 12.0μm ] range at distances of up to 20m . The model is robust against variable atmospheric conditions, and the device is presented together with a quick calibration procedure that allows for in field deployment in rough industrial environments, thus enabling in line measurements. We validate the temperature and emissivity estimates by our device against laboratory equipment under controlled conditions in the [550, 850∘C ] temperature range for two solid samples with well characterized spectral emissivity’s: alumina ( α−Al2O3 ) and hexagonal boron nitride ( h−BN ). The analysis of the results yields Root Mean Squared Errors of 32.3∘C and 5.7∘C respectively, and well correlated spectral emissivity’s.