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赤铁矿竖炉焙烧过程关键被控变量的优化设定值不易获得,使得生产指标难以控制在其目标值范围内。将案例推理、参量预报和专家系统技术相结合,提出一种竖炉焙烧过程的多变量智能优化设定方法。预设定模型给出控制回路的预设定值,案例评价模型和案例修正模型分别对预设定值进行评价和校正,从而实现了控制回路设定值的在线自动调整。实验及应用表明了方法的有效性,能够适应工况的频繁变化,实现了生产指标的优化控制,取得明显成效。
The optimal setting of key controlled variables in hematite shaft furnace roasting process is not easy to obtain, making it difficult to control the production index within its target value. Combining case-based reasoning, parametric forecasting and expert system techniques, a multivariable intelligent optimization setting method for shaft furnace roasting was proposed. The preset model gives the preset value of the control loop, the case evaluation model and the case correction model respectively evaluate and correct the preset value, so as to realize the online automatic adjustment of the control loop set value. Experiments and applications show that the method is effective, able to adapt to frequent changes in working conditions, and achieve the optimal control of production indicators, and achieved remarkable results.