Soft Sensor design for a Sulfur Recovery Unit using Genetic Algorithms

Author

Bella, A. Di ; Fortuna, L. ; Graziani, S. ; Napoli, G. ; Xibilia, M.G.

Author_Institution

Univ. degli Studi di Catania, Catania

fYear

2007

fDate

3-5 Oct. 2007

Firstpage

1

Lastpage

6

Abstract

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.

Keywords

decontamination; design engineering; genetic algorithms; maintenance engineering; process control; production facilities; regression analysis; sensor fusion; sensors; Lipschitz numbers; genetic algorithms; hydrogen sulphide; industrial process; maintenance operation; refinery; regressor selection; soft sensor design; sulfur recovery unit; Algorithm design and analysis; Gas detectors; Genetic algorithms; Hydrogen; Input variables; Monitoring; Refining; Sensor phenomena and characterization; System identification; Tail; Lipschitz numbers; NMA Models; Regressors Selection; Soft Sensors;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Conference_Location

Alcala de Henares

Print_ISBN

978-1-4244-0829-0

Electronic_ISBN

978-1-4244-0830-6

Type

conf

DOI

10.1109/WISP.2007.4447583

Filename

4447583