Professional paper
SOFTWARE SENSORS IN IMPROVING PRODUCT QUALITY AND HDS PROCESS CONTROL
Ivana Lukec
Darko Lukec
Darko Klarić
Abstract
Abstract
Today, we are witnessing the necessity to produce high quality fuels in our refineries. To meet the market needs, refining processes must be equipped with a satisfactory number of process analyzers, which is not always easy, because of their price. In the past ten years, there has been a significant number of software sensors present in the process industry. Their application is based on process model built from process data in order to continuously, on-line, predict physical and chemical properties or product content and improve process monitoring and control.
In this paper, practical application of software sensor based on neural networks was explored on the actual case of sulfur content in the hydrodesulphurization unit product, LGO. The research results shall be applied in practice.
Keywords
HDS catalytic desulfurization; automated, computer controlled process; chemical composition control system; neural network; selflearning control system; selforganizing control system
Hrčak ID:
6531
URI
Publication date:
31.12.2006.
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