Data Analysis and Modelling of Billets Features in Steel Industry

Sensors (Basel). 2022 Sep 27;22(19):7333. doi: 10.3390/s22197333.

Abstract

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.

Keywords: billet; data analysis; modelization; reheating furnace; rolling mill stands; steel industry; tracking system.

MeSH terms

  • Data Analysis*
  • Industry
  • Steel*
  • Temperature

Substances

  • Steel

Grants and funding

This research received no external funding.