Title :
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
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;
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
DOI :
10.1109/WISP.2007.4447583
