The efficiency of soft sensors modelling in advanced control systems in oil refinery through the application of hybrid intelligent data mining techniques

• Published in: Journal of physics. Conference series Vol. 1529; no. 5; pp. 52049 - 52060
• Main Authors: Al-Jlibawi, Ali, Othman, Mohammed Lutfi Bin, Al-Huseiny, Muayed S., Aris, Ishak Bin, Bahari, Samsul
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.05.2020
• Subjects: Complexity; Control systems; Cost analysis; Crude oil; Data analysis; Data mining; Discretization; Flow velocity; Hybrid systems; Laboratories; Missing data; Modelling; Naphtha; Outliers (statistics); Petroleum refineries; Programmable logic controllers; Refineries; Refining; Regression models; Sensors; Set theory; Soft computing; Supervisory control and data acquisition; Virtual sensors

Quality variables cannot be automatically measured to all nor be measured at a high cost, infrequently, nor with high delays, such as laboratory analysis and online analyser. Therefore, data-driven soft sensors are inferential models which use online available sensors, such as temperature, pressure,...