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Soft Sensor design for a Sulfur Recovery Unit using Genetic Algorithms

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5 Author(s)
A. di Bella ; Università degli Studi di Catania, DIEES, Viale A. Doria 6, 95125, Catania ITALY ; L. Fortuna ; S. Graziani ; G. Napoli
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In the paper the Soft Sensor design strategy for an industrial process, via neural NMA model, is described. In details, the hydrogen sulphide (H2S percentage) in the tail stream of a Sulfur Recovery Unit (SRU) of a refinery located in Sicily, Italy, is estimated by a Soft Sensor, that was designed to replace the online analyzer during maintenance operations. A general design strategy, based on the automatic selection of regressors of a NMA model is proposed. It is based on the minimization of the Lipschitz numbers by a Genetic Algorithms (GA) approach. A comparative analysis with an empirical model, developed on the basis of suggestions given by plant experts, is included to show the validity of the proposed procedure.

Published in:

Intelligent Signal Processing, 2007. WISP 2007. IEEE International Symposium on

Date of Conference:

3-5 Oct. 2007