Support Vector Machine-based Soft Sensors in the Isomerisation Process (CROSBI ID 288929)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Herceg, Srečko ; Ujević Andrijić, Željka ; Bolf, Nenad
engleski
Support Vector Machine-based Soft Sensors in the Isomerisation Process
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.
support vector machine, soft sensor, isomerisation process, process analyser
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Podaci o izdanju
34 (4)
2020.
243-255
objavljeno
0352-9568
1846-5153
10.15255/CABEQ.2020.1825