基于RBF网络的醋酸乙烯聚合率软测量研究

A Research on the Soft-Sensing Method of Vinyl Acetate Polymerization Rate Based on RBF Neural Network

针对目前聚乙烯醇生产过程中醋酸乙烯(VAC)聚合率难以在线检测的情况,提出利用RBF神经网络建立VAC聚合率软测量模型,并运用大量实测数据对RBF神经网络进行了训练和仿真.仿真结果表明该方法是有效的,所建模型具有较高的精度和良好的泛化能力.

Aiming at the difficulty in measuring the vinyl acetate（VAC）polymerization rate on-line in the process of polyvinyl alcohol production, a VAC polymerization rate soft-sensing model is established based on RBF neural network in this paper. The RBF neural network is trained and simulated by tons of practical data, the simulation results show that the method is effective and the established model offers high accuracy and excellent capability of generalization.