球团链篦机篦床温度多物理场时空耦合与协同控制机理研究

Grate is one of the key equipment for pellet production. The grate bed temperature equilibrium stability control is the important factor for efficient use of energy, good quality of the pellets and prolonging the service life of grate. Considering the complex formation mechanism and the various influence factors, we studied the mechanism of the multi-physical field spatial and temporal coupling including temperature field, flow field, and pressure field. Then a multiple physical field coupling mathematical model of grate bed temperature was established based on the k-E turbulence, eddy dissipation, fluid-solid coupling heat transfer theory. With the help of CFD and FLUENT, the simulation of grate bed temperature multi-physics coupling was conducted to analysis the influence of grate bed temperature multi-physics coupling on pellet preheating and drying process. The method of orthogonal test was employed to establish the pellet preheating and drying heat matching model and determine the parameters of preheating and drying processes. The grate bed temperature field synergy control strategy was proposed based on spatiotemporal coupling fuzzy logic system, and the grate bed temperature field fuzzy cooperative control model was established by using the method of system identification. At last, the grate bed temperature field spatial and temporal coupling fuzzy collaborative controller was designed and the grate bed temperature field multiple control source spatial and temporal coupling fuzzy collaborative monitoring and control system was constructed to verify the stability and robustness of the control system. The research can provide scientific basis for grate bed temperature field stability and accurate control problem, promoting our pellet production equipment to the development direction of large, intelligent, energy saving and environmental protection.

链篦机是球团生产的关键设备。篦床温度场均衡稳定控制是有效利用能源、保证球团质量和延长链篦机使用寿命的重要因素。针对篦床温度场形成机理复杂，影响因素繁多，研究球团链篦机篦床温度场与气流速度场和气压场的多物理场时空耦合机理，依据k-E湍流、涡耗散、流固耦合传热等理论建立篦床温度多物理场时空耦合数学模型；基于CFD和FLUENT对篦床温度多物理场时空耦合数值模拟，分析温度多物理场分布变化规律，对球团干燥预热过程中的破裂和氧化还原速度等影响；通过热能匹配正交实验建立球团干燥预热热能匹配模型，通过正交试验方法优化确定球团干燥预热热工工艺参数；提出基于时空耦合模糊逻辑系统的篦床温度场协同控制策略，采用系统辨识方法建立篦床温度多物理场时空耦合协同控制数学模型，构建多控制源时空耦合协同控制试验系统，试验分析篦床温度场均衡稳定控制效果，验证系统稳定性和鲁棒性，为实现球团安全高效干燥预热生产提供科学依据。

链篦机温度场其状态、输出及参数等不仅在时间域内动态变化，也随空间变化，受气流速度场和气压场的关联作用，属于时空耦合复杂系统。实现球团链篦机温度场均衡稳定的控制，是我国现代球团生产企业有效降低能源消耗、提高球团生产质量和链篦机使用寿命、提升综合经济效益所必须面对的、且急需解决的问题。 . 本项目以球团链篦机温度场时空耦合复杂系统为研究对象，通过理论建模，仿真分析以及实验研究全面深入地研究了链篦机温度场时空耦合机理，提出了链篦机温度场协同稳定控制方法。. 主要的研究成果有：分析了多参数对链篦机运行过程中温度场的影响规律，通过正交试验，探明了影响链篦机温度场的主要因素；基于CFD-DEM耦合模拟了球团的干燥过程，并通过破裂系数建立了球团干燥速率与破裂率的关系；提出并定义了有效热能利用率和干燥度两个指标的评价体系，计算得到了优化后的热工参数组合，该参数组合下的干燥段有效热能利用率提高了7.31%，球团料层的干燥度提高了5.51%；建立了磁铁矿（Fe3O4）与氧气分子相互作用模型以及单个球团等温氧化模型，探明了链篦机温度场对球团物化性质的作用机制；提出了链篦机温度场多变量模糊自适应神经网络控制策略；基于贝叶斯-BP神经网络系统辨识的球团链篦机预热段温度场模型的预测误差约为0.014K，拟合度R≈0.99，预测相对误差在4%范围内。研制了多物理场分布检测与动态耦合过程控制试验系统，编写了温度、压力、流量等多物理场试验的实时监控软件，采集和控制多物理场试验过程中的众多热工参数，基于该试验系统可以模拟链篦机球团干燥和预热的运行过程。. 本项目研究成果为环境友好、资源节约和能源高效利用的球团生产提供了科学依据，促进了球团产业的节能降耗和可持续发展。