| Titre : | Online data reconciliation with poor redundancy systems (2012) |
| Auteurs : | Flavio Manenti, Auteur ; Maria Grazia Grottoli, Auteur ; Sauro Pierucci, Auteur |
| Type de document : | Article : texte imprimé |
| Dans : | Industrial & engineering chemistry research (Vol. 50 N° 24, Décembre 2011) |
| Article en page(s) : | pp. 14105-14114 |
| Note générale : | Chimie industrielle |
| Langues : | Anglais |
| Tags : | Data reconciliation |
| Résumé : | The paper deals with the integrated solution of different model-based optimization levels to face the problem of inferring and reconciling online plant measurements practically, under the condition of poor measure redundancy, because of a lack of instrumentation installed in the field. The novelty of the proposed computer-aided process engineering (CAPE) solution is in the simultaneous integration of different optimization levels: (i) the data reconciliation based on a detailed process simulation; (ii) the introduction and estimation of certain adaptive parameters, to match the current process conditions as well as to confer a certain generality on it; and (iii) the use of a set of efficient optimizers to improve plant operations. The online feasibility of the proposed CAPE solution is validated on a large-scale sulfur recovery unit (SRU) of an oil refinery. |
| DEWEY : | 660 |
| ISSN : | 0888-5885 |
| En ligne : | http://cat.inist.fr/?aModele=afficheN&cpsidt=25299879 |
