Izvorni znanstveni članak
https://doi.org/10.15255/CABEQ.2020.1825
Support Vector Machine-based Soft Sensors in the Isomerisation Process
S. Herceg
; Faculty of Chemical Engineering and Technology, University of Zagreb, Department of Measurements and Process Control, Savska c. 16/5a, 10 000 Zagreb, Croatia
Ž. Ujević Andrijić
; Faculty of Chemical Engineering and Technology, University of Zagreb, Department of Measurements and Process Control, Savska c. 16/5a, 10 000 Zagreb, Croatia
N. Bolf
; Faculty of Chemical Engineering and Technology, University of Zagreb, Department of Measurements and Process Control, Savska c. 16/5a, 10 000 Zagreb, Croatia
Sažetak
This paper presents the development of soft sensor empirical models using support vector machine (SVM) for the continual assessment of 2,3-dimethylbutane and 2-methylpentane mole percentage as important product quality indicators in the refinery isomerisation process. During the model development, critical steps were taken, including selection and pre-processing of the industrial process data, which are broadly discussed in this paper. The SVM model results were compared with dynamic linear output error model and nonlinear Hammerstein-Wiener model. Evaluation of the developed models on independent data sets showed their reliability in the assessment of the component contents. The soft sensors are to be embedded into the process control system, and serve primarily as a replacement during the process analysers’ failure and service periods.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Ključne riječi
support vector machine; soft sensor; isomerisation process; process analyser
Hrčak ID:
251482
URI
Datum izdavanja:
3.2.2021.
Posjeta: 1.186 *