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Data Analysis and Modelling of Billets Features in Steel Industry

This study proposes a data analysis and modelization method for the rolling mill process of billets in steel plants. By exploiting rolling mill signals and advanced data processing algorithms, a reliable billet tracking system is designed, which tracks each workpiece from the furnace entrance to the...

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Autores principales: Zanoli, Silvia Maria, Pepe, Crescenzo, Moscoloni, Elena, Astolfi, Giacomo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572753/
https://www.ncbi.nlm.nih.gov/pubmed/36236432
http://dx.doi.org/10.3390/s22197333
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author Zanoli, Silvia Maria
Pepe, Crescenzo
Moscoloni, Elena
Astolfi, Giacomo
author_facet Zanoli, Silvia Maria
Pepe, Crescenzo
Moscoloni, Elena
Astolfi, Giacomo
author_sort Zanoli, Silvia Maria
collection PubMed
description This study proposes a data analysis and modelization method for the rolling mill process of billets in steel plants. By exploiting rolling mill signals and advanced data processing algorithms, a reliable billet tracking system is designed, which tracks each workpiece from the furnace entrance to the rolling mill stands’ exit area. Based on the stored information, two problems are addressed: the data analysis of the temperature sensors (a thermal imaging camera and pyrometers) and the current that is related to the rolling mill stands’ absorption, and subsequently, a mathematical modelization of the billets’ temperature along their path in the rolling mill is produced. The data analysis suggested that we should perform hardware modifications: the thermal imaging camera was repositioned to avoid the effect of scale formation on the temperature measurements. The modelization phase provided the basis for future control and/or diagnosis applications that will exploit a temperature decay model.
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spelling pubmed-95727532022-10-17 Data Analysis and Modelling of Billets Features in Steel Industry Zanoli, Silvia Maria Pepe, Crescenzo Moscoloni, Elena Astolfi, Giacomo Sensors (Basel) Article This study proposes a data analysis and modelization method for the rolling mill process of billets in steel plants. By exploiting rolling mill signals and advanced data processing algorithms, a reliable billet tracking system is designed, which tracks each workpiece from the furnace entrance to the rolling mill stands’ exit area. Based on the stored information, two problems are addressed: the data analysis of the temperature sensors (a thermal imaging camera and pyrometers) and the current that is related to the rolling mill stands’ absorption, and subsequently, a mathematical modelization of the billets’ temperature along their path in the rolling mill is produced. The data analysis suggested that we should perform hardware modifications: the thermal imaging camera was repositioned to avoid the effect of scale formation on the temperature measurements. The modelization phase provided the basis for future control and/or diagnosis applications that will exploit a temperature decay model. MDPI 2022-09-27 /pmc/articles/PMC9572753/ /pubmed/36236432 http://dx.doi.org/10.3390/s22197333 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zanoli, Silvia Maria
Pepe, Crescenzo
Moscoloni, Elena
Astolfi, Giacomo
Data Analysis and Modelling of Billets Features in Steel Industry
title Data Analysis and Modelling of Billets Features in Steel Industry
title_full Data Analysis and Modelling of Billets Features in Steel Industry
title_fullStr Data Analysis and Modelling of Billets Features in Steel Industry
title_full_unstemmed Data Analysis and Modelling of Billets Features in Steel Industry
title_short Data Analysis and Modelling of Billets Features in Steel Industry
title_sort data analysis and modelling of billets features in steel industry
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572753/
https://www.ncbi.nlm.nih.gov/pubmed/36236432
http://dx.doi.org/10.3390/s22197333
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