Parex过程基于神经网络简化模型的操作优化
Operation Optimization of Parex Process Based on Neural Networks Model
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摘要: 以芳烃吸附Parex过程为例,在建立其稳态机理模型的基础上,采用正交设计方法获得了 特性数据;根据这些数据建立具有一个隐层的神经网络模型,并以此作为优化操作的简化模型。采用一种新的优化方法,得到吸附塔的最佳操作条件,以实现计算机的二级优化控制。Abstract: Taking the adsorption column of a petrochemical plant for the case study,based on characteristic data which is obtained from the mechanism steady-state model by means of orthonormal design method,the artificial neural networks model is investigated.The operation condition of this column is optimized by a new optimization method SAGACIA,The result is satisfactory,and the enterprise will gain more economical benefit.