Data Fusion Based Quality Monitoring and Control of Strip Thickness

Abstract:

This paper first introduces the principle of AGC and conventional AGC in Hot Strip Mill (HSM). A linearized and discretized state-space model used for rolling force and thickness control is obtained by using recursive squares method. A data fusion algorithm based on Kalman filter is presented. For hot strip systems with complex multi-variables, an asynchronous fusion estimation algorithm is built and applied to the thickness prediction of the hot strip mill and the plasticity coefficient Q of strip prediction. Finally, real-time prediction on thickness and plasticity coefficient of the coming strip is synthetically utilized in hot strip rolling thickness control system, to improve the quality of final coming strip thickness.

• Periodical: Advanced Materials Research (Volumes 230-232)
• Pages: 266-273
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.230-232.266
• Online since: May 2011
• Authors: Kai Xiang Peng, Dong Hua Zhou
• Keywords: AGC, Data Fusion, Hot Strip Mill, Plasticity Coefficient, Quality Monitoring

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