常减压装置初馏塔顶产品干点软测量的应用研究

Study on soft-sensing model of dry point of the atmospheric-vacuum primary dis-tillation tower

在常减压装置中,影响初馏塔顶石脑油干点的因素很多,反应十分复杂,故难以建立准确的机理模型。针对传统的主元分析法(PCA)或自适应模糊推理系统(ANFIS)建立软测模型中的缺点,本文提出采用主元分析法预处理输入变量,再结合自适应模糊推理系统,进行常减压装置初馏塔顶石脑油干点的软测量模型的改进,能及时测定化工过程的变量,对稳定生产过程,有效控制产品质量具有重要意义。通过MATLAB仿真,表明该改进型方法的软测建模效果较好,建模的训练时间大大节省了,且泛化能力和拟合精度很好。

It is hard to get the satisfied mechanism model in the atmospheric distillation unit for complicated influential factors and complicated reactive mechanism. Principle component analysis（PCA） is used to deal with the input variables, and the adaptive neural fuzzy inferential system（ANFIS） is applied to build soft sensor modeling of dry point in the atmospheric distillation unit. It is well known that to measure and estimate the chemical process variables in time had vital significance in ensuring process stabilization, and effectively controlling its product quality. The result indicates that the PCA-ANFIS approach can not only have good generalization capacity and good prediction accuracy,but also decreases the training time of this model via MATLAB simulation.