基于改进鱼群算法的铝热连轧摩擦系数模型研究

Study on Friction Coefficient of Aluminum Hot Rolling Model Based on Improved Fish Swarm Algorithm

铝热连轧机二级过程自动化中，存在变形区摩擦系数预报精度低的问题。通过定量分析油膜厚度、轧制温度和摩擦系数的关系，运用改进的鱼群算法回归并建立起了针对轧制现场的摩擦系数模型。将上述模型应用到铝热连轧机结果表明，新模型提高了摩擦系数的软测量精度，提高了轧制的稳定性，对以摩擦系数为基础的其他轧制模型起到了参考作用。

In the level 2 process automation of hot rolling, there is a problem of low forecast accuracy of friction coefficient in the deformation zone. A quantitative relationship between the oil film thickness, the rolling temperature and the coefficient are analyzed. The model of friction coefficient which is more suitable for the scene of the roiling is established through the improved artificial fish swarm algorithm. The above model is applied to the aluminum strip machine and the results show that the new model improved the soft measurement precision of the friction coefficient, the stability of rolling and played a reference role in the other model base on the model of the friction coefficient.