Optimization of continuous variable crown work roll shifting strategy using k‐nearest neighbors algorithm for hot strip rolling mill

Abstract

Abstract Appropriate work roll shifting strategy in the finishing hot strip mill can make roll wear uniform and contour smooth. To eliminate the problem of roll shifting position duplication due to available roll shifting strategy, the optimized work roll shifting strategy is proposed in the hot strip rolling mill with continuous variable crown work rolls, using the k‐nearest neighbors algorithm. The self‐perpetuating parameter is used to describe the concentrated wear of the work roll. The position repeated parameter is put forward to evaluate the roll shifting position history. The relationship between concentrated shifting positions and uneven roll wear is analyzed based on in‐site data collected in a hot strip rolling mill. The program of optimization strategy is coded using language C. Off‐line simulation is made to obtain optimized shifting positions using the program. The comparison between in‐site engineering data and optimized shifting positions has been assessed using the scatter diagram and kernel density estimation. Comparison results show that the new strategy can solve the problem of shifting position duplication well. A simplified method is established to make it easy to apply the strategy to online applications, and the in‐site application shows that the optimization strategy has an excellent practical effect.

Keywords

• hot strip
• k‐NN algorithm
• online application
• optimization
• roll shifting strategy