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熱連軋粗軋區FES寬展模型及其優化

FES width spread model and its optimization for a rough rolling mill

  • 摘要: 為了滿足某廠1580熱連軋機寬度控制精度需求,提高寬展模型的廣泛適用性,利用ANSYS/LS-DYNA有限元軟件,對熱軋粗軋區立軋-平軋過程進行了模擬.根據模擬數據,系統地分析了軋件寬度、厚度、軋輥直徑、立輥側壓量和厚度壓下量對"狗骨"寬展、自然寬展和絕對寬展的影響規律.利用模擬數據并結合現場數據構造了FES(finite element simulation)"狗骨"寬展模型和自然寬展模型,并建立了PSO-BP神經網絡(粒子群BP神經網絡).最后,FES寬展模型與PSO-BP神經網絡相結合預報第1、3和5道次的寬展,其預報值與實測值誤差在1mm以內的均達到了99%以上,達到了寬度控制的精度要求.

     

    Abstract: In order to meet the need of width control precision for a 1580 hot strip mill and to improve the applicability of width spread models,the process of edge rolling-horizontal rolling in the rough rolling area was simulated by the finite element software ANSYS/LS-DYNA.The effects of width,thickness,roll diameter,reduction in width and reduction in thickness on ‘dog-bone’ width spread,natural width spread and absolute width spread were studied.The FES models of ‘dog-bone’ width spread and natural width spread were established with simulating data and field data,and the PSO-BP neural network was founded.At last,the FES width spread models were combined with the PSO-BP neural network to predict the width spread of the first,third and fifth pass.The percentage of the case that the error between predicted data and the measured values is less than 1 mm was more than 99%,and the width control precision was satisfied.

     

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