| Titre : | Application of principal component analysis for monitoring and disturbance detection of a hydrotreating process (2008) |
| Auteurs : | Stella Bezergianni, Auteur ; Aggeliki Kalogianni, Auteur |
| Type de document : | Article : texte imprimé |
| Dans : | Industrial & engineering chemistry research (Vol. 47 N°18, Septembre 2008) |
| Article en page(s) : | p. 6972–6982 |
| Note générale : | Chemical engineering |
| Langues : | Anglais |
| Tags : | Principal component analysis Multivariate process |
| Résumé : | Principal component analysis (PCA) is a well-established technique for monitoring and disturbance detection of multivariate process, as it enables variability assessment through dimensionality reduction. PCA was applied to a hydroprocessing pilot plant to monitor the overall process variability. Contribution plots around points of increased variability were used to analyze process variability and its association with process variables. The methodology monitored successfully the set of 38 variables and diagnosed significant disturbances and their causes. |
| En ligne : | http://pubs.acs.org/doi/abs/10.1021/ie0714605 |
