生料浆配料过程磨机负荷的混合智能控制

Hybrid Intelligent Control of Mill Load in the Blending Process of Raw Slurry

针对在氧化铝生料浆配料过程中难以采用常规方法来控制磨机负荷状态的问题,提出了由负荷状态估计模型和负荷调整模型组成的磨机负荷混合智能控制方法.负荷状态估计模型根据磨机的振动与电流信号,采用规则推理方法估计出磨机的负荷状态.负荷调整模型采用案例推理方法自动调节磨机给料量,将负荷控制在合适范围内.该方法成功应用于某氧化铝厂生料浆配料过程中,长期运行结果表明,提高了磨机台时产能,减少了"堵磨"故障发生次数,提高了生产效率并节能降耗.

In the blending process of raw slurry in alumina production, it is difficult to control the mill load state with the traditional approaches. A hybrid intelligent control approach of mill load is proposed, which is composed of the estimation model of mill load state and the adjustment model of mill load. Based on the vibration and electric current, the mill load state is estimated by the estimation model where rule-based reasoning is adopted. The total amount of fed materials is adjusted automatically by the adjustment model where case-based reasoning is adopted. Therefore, the mill load can be controlled within an appropriate range. The proposed approach is ;applied to the blending process of raw slurry in an alumina factory. A long-term running results show that the production capacity of mill is increased, the mill blockage is decreased, and high production efficiency and energy saving can also be achieved.