Long- and Short-Term Self-Learning Models of Rolling Force in Rolling Process Without Gaugemeter of Plate

Abstract

Owing to a lack of gaugemeter and the variety of steel grades and standards in some plate mills, the long-and short-term self-learning models of rolling force based on gauge soft-measuring with high precision were brought up. The soft-measuring method and target value locked method were used in these models to confirm the actual exit gauge of passes, and thick layer division and exponential smoothing method were used to dispose the deformation resistance parameter, which could be calculated from the actual data of the rolling process. The correlative mathematical methods can also be adapted to self-learning with gaugemeter. The models were applied to the process control system of AGC (automatic gauge control) reconstruction on 2 800 mm finishing mill of Anyang steel and favorable effect was obtained.