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Soft sensor design for a Sulfur Recovery Unit using a clustering based approach

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3 Author(s)
Graziani, S. ; DIEES, Univ. degli Studi di Catania, Catania ; Napoli, G. ; Xibilia, M.G.

In the paper a soft sensor design strategy for an industrial process, via neural NMA model, is described. 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 cost function of a Gath Geva clustering algorithm. The obtained soft sensor will be implemented in a refinery in order to replace the measurement device during maintenance to guarantee continuity in the monitoring and control of the plant.

Published in:

Instrumentation and Measurement Technology Conference Proceedings, 2008. IMTC 2008. IEEE

Date of Conference:

12-15 May 2008