Whole process prediction model of silicon steel strip on transverse thickness difference based on Takagi-Sugeno fuzzy network

The hot rolling and cold rolling control models of silicon steel strip were examined. Shape control of silicon steel strip of hot rolling was a theoretical analysis model, and the shape control of cold rolling was a data-based prediction model. The mathematical model of the hot-rolled silicon steel section, including the crown genetic model, inter-stand crown recovery model, and hot-rolled strip section prediction model, is used to control the shape of hot-rolled strip. The cold rolling shape control is mainly based on Takagi-Sugeno fuzzy network, which is used to simulate and predict the transverse thickness difference of cold-rolled silicon steel strip. Finally, a predictive model for the transverse thickness difference of silicon steel strips is developed to provide a new quality control method of transverse thickness of combined hot and cold rolling to improve the strip profile quality and increase economic efficiency. The qualified rate of the non-oriented silicon steel strip is finally obtained by applying this model, and it has been steadily upgraded to meet the needs of product quality and flexible production.