On-line Estimation of the Product Qualities for Atmospheric Tower Based on Nonlinear Principal Component Analysis

A new soft sensor based on nonlinear principal component analysis (PCA)is developed.A three-layer feed-forward neural network model is established to approximate the relationship between the scores of the nonlinear principal components and the estimated variable.The proposed method is applied on an industrial crude oil atmospheric distillation tower and illustrated by comparisons with other familiar methods.The results show that the proposed method gives a better performance over the conventional PCA method and neural network method.