A Multiblock Approach to Fuse Process and Near-Infrared Sensors for On-Line Prediction of Polymer Properties - Université de Lille Accéder directement au contenu
Article Dans Une Revue Sensors Année : 2022

A Multiblock Approach to Fuse Process and Near-Infrared Sensors for On-Line Prediction of Polymer Properties

L. Strani
  • Fonction : Auteur
D. Tanzilli
  • Fonction : Auteur
F. Bonacini
  • Fonction : Auteur
A. Perolo
  • Fonction : Auteur
E. Mantovani
  • Fonction : Auteur
A. Ferrando
  • Fonction : Auteur
M. Cocchi
  • Fonction : Auteur

Résumé

Petrochemical companies aim at assessing final product quality in real time, in order to rapidly deal with possible plant faults and to reduce chemical wastes and staff effort resulting from the many laboratory analyses performed every day. In order to answer these needs, the main purpose of the current work is to explore the feasibility of multiblock regression methods to build real-time monitoring models for the prediction of two quality properties of Acrylonitrile-Butadiene-Styrene (ABS) by fusing near-infrared (NIR) and process sensors data. Data come from a production plant, which operates continuously, and where four NIR probes are installed on-line, in addition to standard process sensors. Multiblock-PLS (MB-PLS) and Response-Oriented Sequential Alternation (ROSA) methods were here utilized to assess which of such sensors and plant areas were the most relevant for the quality parameters prediction. Several prediction models were constructed exploiting measurements provided by sensors active at different ABS production process stages. Both methods provided good prediction performances and permitted identification of the most relevant data blocks for the quality parameters’ prediction. Moreover, models built without considering recordings from the final stage of the process yielded prediction errors comparable to those involving all available data blocks. Thus, in principle, allowing final ABS quality to be estimated in real-time before the end of the process itself.
Fichier principal
Vignette du fichier
sensors-22-01436-v2.pdf (3.17 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-04512546 , version 1 (20-03-2024)

Licence

Paternité

Identifiants

Citer

L. Strani, Raffaele Vitale, D. Tanzilli, F. Bonacini, A. Perolo, et al.. A Multiblock Approach to Fuse Process and Near-Infrared Sensors for On-Line Prediction of Polymer Properties. Sensors, 2022, Sensors, 22, ⟨10.3390/s22041436⟩. ⟨hal-04512546⟩
0 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More