Statistical Estimation Model for Product Quality of Petroleum

Controls of the temperature, pressure and flowing quantity are important for the stable operation of the product quality in the distillation tower. The usual measuring way of product quality estimation is made by the off-line analysis. In this paper, online estimation method of product quality is studied for improving the product quality. The estimation method based on stochastic analysis was developed for online estimation. In this paper, the data of temperature, pressure and flow volum in the distillation tower are treated. As the estimation models, RNN (Recurrent Neural Net Work) and PLS (Partial Least Square Regression Method) were adopted. The actual plant data were used in the analysis. Both PLS and RNN models could compensate each other to improve the accuracy in estimation.