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Composition Prediction of Debutanizer Column using Neural Network

Isnu, Ima Syafiah (2015) Composition Prediction of Debutanizer Column using Neural Network. IRC, Universiti Teknologi PETRONAS. (Unpublished)

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Abstract

In oil refining industries, debutanizer column is one of the important unit operations. Debutanizer column is the main column used to produce the main product in oil refinery process. The online composition prediction of top and bottom product of debutanizer column using neural network will be an aid to increase product quality monitoring in oil refining industry. In this work, a single dynamic neural network model is used in order to achieve the objective which is to generate composition prediction online of the top and bottom product of debutanizer column. Neural network is a computing system with several of simple and highly interconnected processing elements that will process information using their dynamic state response to external inputs. It is a software based sensor method or known as “soft sensor” which is a helpful technology that utilizes software techniques to infer the value of important but difficult-to-measure process variables from available process variables which are requisite from physical sensor observation or lab measurements. The neural network development and equation based model for ibutane, i-pentane, n-butane, n-pentane and propane has been obtained. Then, these results will be compared with proportional integral derivatives (PID) controller design to show its supremacy over this method.

Item Type: Final Year Project
Academic Subject : Academic Department - Chemical Engineering - Separation Process
Subject: T Technology > TP Chemical technology
Divisions: Engineering > Chemical
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 02 Nov 2015 15:58
Last Modified: 25 Jan 2017 09:35
URI: http://utpedia.utp.edu.my/id/eprint/15812

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