Research on the Strategy of Delay Rolling for Reheating Furnace based on Swarm Intelligence Algorithm

Xu, Zhengguang; Tong, Hua; Fan, Xingyuan; Zhu, Xu

doi:10.1109/icsp54964.2022.9778733

Cited by 2 publications

(1 citation statement)

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“…A regression dependence of the steel billet temperature that is based on its furnace heating history is obtained. In [ 24 ], a mathematical model of the billet heating process in a regenerative reheating furnace is established to predict the state of the billets in the furnace after a period of delay rolling. An adaptive genetic algorithm and a particle swarm optimization algorithm are used, and the results of these are compared.…”

Section: Introductionmentioning

confidence: 99%

Data Analysis and Modelling of Billets Features in Steel Industry

Zanoli

Pepe

Moscoloni³

et al. 2022

Sensors

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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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Section: Introductionmentioning

confidence: 99%