Distillation End Point Estimation in the Diesel Fuel Production (CROSBI ID 176276)
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Mohler, Ivan ; Ujević Andrijić, Željka ; Bolf, Nenad ; Galinec, Goran
engleski
Distillation End Point Estimation in the Diesel Fuel Production
Soft sensors for the on-line estimation of 95% distillation point (D95) of diesel fuel in crude distillation unit (CDU) are developed. Experimental data are acquired from the refinery distributed control system (DCS) and include on-line available continuously measured variables and laboratory assays. Soft sensors are developed using different linear and nonlinear identification methods. Additional laboratory data for the model identification are generated by Multivariate Adaptive Regression Splines (MARSplines). The models are evaluated based on Root Mean Square Error (RMS), Absolute Error (AE), FIT and Final Prediction Error (FPE) criteria. Among the variety of models, the best results are achieved with Box Jenkins (BJ), Output Error (OE) and Hammerstein–Wiener (HW) model. Based on developed soft sensors it is possible to estimate fuel properties in continuous manner and apply inferential control. By the real plant application of developed soft sensors considerable savings could be expected, as well as compliance with strict law regulations for product quality specifications.
crude distillation unit; distillation end point; soft sensor; process identification
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