Model-based control of the dynamics during fine grinding in wet-operated stirred media mills

搅拌介质粉碎机用于各种超细粉碎过程。所选择的操作参数与悬浮特性相结合，决定了研磨介质的动能，在连续操作的情况下，还决定了颗粒的传输以及研磨介质在磨机内的不均匀轴向分布。这决定了粉碎行为和能耗。为了对产品颗粒进行超细粉碎，细化到纳米级，磨机通常使用搅拌容器进行循环操作。相应地，搅拌槽和磨机内的粒度分布会发生动态变化。由于比表面积随着颗粒尺寸的减小而不断增大，颗粒间的相互作用及其对悬浮稳定性和粘度的影响在超细粉碎中起着基础性的作用。悬浮液粘度的增加直接影响研磨介质的相对速度，从而影响传递给产品颗粒的能量。此外，悬浮液粘度还会影响磨矿介质的轴向分布，从而影响磨矿介质的运动行为。因此，除了控制搅拌器喷嘴速度或流量外，工艺控制中还必须考虑静电或立体稳定添加剂。此外，随着颗粒大小的变化，理想颗粒破碎所需的应力能量，即磨机的最佳工作点，向较低的应力能量转移。在湿式磨机中控制细磨过程时，必须考虑磨矿介质因粘度增加而产生的减振、颗粒强度随粒度减小而增大以及由于应力强度增大而使最佳工作点移动之间的相互作用。最后，自发团聚或再结晶过程对在线测量技术和过程控制提出了很高的要求。虽然存在搅拌介质磨机的快捷模型和建模方法，但目前还没有模型允许动态控制关于粒度分布、最佳能量利用或最大生产率的细碎过程的变化。在这个项目中寻求的一种控制的可能性是通过人口平衡模型(PBM)与非线性模型预测控制(NMPC)策略相结合的描述。因此，将通过机械粉碎模型来描述PBM。

Stirred media mills are used in various ultra-fine comminution processes. The selected operating parameters in combination with the suspension properties determine the kinetic energy of the grinding media and, in the case of continuous operation, also the transport of the particles as well as the non-uniform axial distribution of the grinding media within the mill. This determines comminution behavior and power consumption. For ultra-fine comminution of the product particles down to the nanoscale, mills are often circuit-operated with an agitated vessel. Hereby, the particle size distributions in the agitated vessel and mill change dynamically. Due to a constant in-crease in specific surface area with decreasing particle size, particle interactions and their influence on suspension stability and viscosity play a fundamental role in ultra-fine comminution. The increase in suspension viscosity has a direct influence on the relative grinding media velocity and thus on the energy transferred to the product particles. In addition, the suspension viscosity influences the axial distribution and thus the movement behavior of the grinding media. Hence, electrostatically or sterically stabilizing additives must be considered in the process control in addition to the control of, e.g., stirrer tip speed or flow rate. Moreover, with changing particle size, the stress energy required for ideal particle breakage, i.e. the optimal operating point of the mill, shifts towards lower stress energies. When controlling a fine grinding process in a wet-operated mill, the interplay between damping of the grinding media through the increase in viscosity, in-crease in particle strength with decreasing particle size and shift in the optimum operating point due to the increase in stress intensity must be considered. Finally, spontaneous reagglomeration or recrystallization processes place high demands on online measurement technology and process control. Although short-cut models and modelling approaches for stirred media mills exist, there currently is no model that allows for dynamic control of changing fine comminution processes with regard to particle size distribution, optimum energy utilization, or maximum production rate. One possibility of control also pursued in this project is the description via population balance models (PBM) in combination with a Nonlinear Model Predictive Control (NMPC) strategy. Thereby the PBM will be described via a mechanistic comminution modell.