Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30382
Soft-Sensor for Estimation of Gasoline Octane Number in Platforming Processes with Adaptive Neuro-Fuzzy Inference Systems (ANFIS)

Authors: Hamed.Vezvaei, Sepideh.Ordibeheshti, Mehdi.Ardjmand

Abstract:

Gasoline Octane Number is the standard measure of the anti-knock properties of a motor in platforming processes, that is one of the important unit operations for oil refineries and can be determined with online measurement or use CFR (Cooperative Fuel Research) engines. Online measurements of the Octane number can be done using direct octane number analyzers, that it is too expensive, so we have to find feasible analyzer, like ANFIS estimators. ANFIS is the systems that neural network incorporated in fuzzy systems, using data automatically by learning algorithms of NNs. ANFIS constructs an input-output mapping based both on human knowledge and on generated input-output data pairs. In this research, 31 industrial data sets are used (21 data for training and the rest of the data used for generalization). Results show that, according to this simulation, hybrid method training algorithm in ANFIS has good agreements between industrial data and simulated results.

Keywords: Adaptive Neuro-Fuzzy Inference Systems, GasolineOctane Number, Soft-sensor, Catalytic Naphtha Reforming

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1058211

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1822

References:


[1] Guilandoust MT, Morris AJ, Tham MT. Adaptive inferential control.Proceedings of IEE Part D 1987;134(3):171-9
[2] Montague GA, Morris AJ, Tham MT.Enhancing bioprocess operability withgeneric software sensors. Journal of Biotechnology 1992;25:183-201H.
[3] A. L. Huebner, "Tutorial: Fundamentals of Naphtha Reforming," AIChE Spring Meeting 1999, Houston, TX, 14-18 March 1999.
[4] DAVID S. J. "STAN" JONES "Handbook of Petroleum Processing".2006 Springer
[5] Mark Lapinski, Lance Baird, and Robert James"HANDBOOK OF PETROLEUM REFINING PROCESSES" 2004 The McGraw-Hill Companies.
[6] Wang S, Jin X. Model-based optimal control of VAV air -conditioning system using genetic algorithm. Building and Environment 2000;35(6):471-87.
[7] Evren Guner."Adaptive NeURO-Fuzzy Inference Systems Applications in Chemical Processes" a Thesis Submitted to the graduate school of natural and applied Sciences the middle east Technical University