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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-9572753 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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