Multivariate image analysis (MIA) for industrial flare combustion control / David Castiñeira in Industrial & engineering chemistry research, Vol. 51 N° 39 (Octobre 2012)  

Public ISBD [article]  inIndustrial & engineering chemistry research > Vol. 51 N° 39 (Octobre 2012) . - pp. 12642-12652 Titre : Multivariate image analysis (MIA) for industrial flare combustion control Type de document : texte imprimé Auteurs : David Castiñeira, Auteur ; Blake C. Rawlings, Auteur ; Thomas F. Edgar, Auteur Année de publication : 2012 Article en page(s) : pp. 12642-12652 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Combustion Image analysis Résumé : A new approach for flare monitoring is proposed so that flare combustion efficiency can be predicted online in industrial plants. Multivariate image analysis (MIA), which is based on principal component analysis (PCA) and projection to latent structures (PLS), has been applied to flare combustion systems in order to predict their resulting combustion efficiencies as a function of the crosswind velocity, using simulated results, and as a function of steam or air flow rates, using experimental tests of a full-size flare. The results show that a multivariate regression model based on flare color images can be used to predict the flare performance over a range of operating conditions for steam-assisted flares. Therefore, simple two-dimensional color images of industrial flares may be a fast, accurate, and inexpensive approach for online monitoring of these industrial combustion systems. This would allow for developing effective flare control and mitigation strategies. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26419219 [article] Multivariate image analysis (MIA) for industrial flare combustion control [texte imprimé] / David Castiñeira, Auteur ; Blake C. Rawlings, Auteur ; Thomas F. Edgar, Auteur . - 2012 . - pp. 12642-12652. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 39 (Octobre 2012) . - pp. 12642-12652 Mots-clés : Combustion Image analysis Résumé : A new approach for flare monitoring is proposed so that flare combustion efficiency can be predicted online in industrial plants. Multivariate image analysis (MIA), which is based on principal component analysis (PCA) and projection to latent structures (PLS), has been applied to flare combustion systems in order to predict their resulting combustion efficiencies as a function of the crosswind velocity, using simulated results, and as a function of steam or air flow rates, using experimental tests of a full-size flare. The results show that a multivariate regression model based on flare color images can be used to predict the flare performance over a range of operating conditions for steam-assisted flares. Therefore, simple two-dimensional color images of industrial flares may be a fast, accurate, and inexpensive approach for online monitoring of these industrial combustion systems. This would allow for developing effective flare control and mitigation strategies. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26419219

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