Dynamic grey-box modeling for online monitoring of extrusion viscosity

Xueqin Liu, Kang Li, Marion McAfee, Bao Kha Nguyen, Gerard McNally

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)
449 Downloads (Pure)


Melt viscosity is a key indicator of product quality in polymer extrusion processes. However, real time monitoring and control of viscosity is difficult to achieve. In this article, a novel “soft sensor” approach based on dynamic gray-box modeling is proposed. The soft sensor involves a nonlinear finite impulse response model with adaptable linear parameters for real-time prediction of the melt viscosity based on the process inputs; the model output is then used as an input of a model with a simple-fixed structure to predict the barrel pressure which can be measured online. Finally, the predicted pressure is compared to the measured value and the corresponding error is used as a feedback signal to correct the viscosity estimate. This novel feedback structure enables the online adaptability of the viscosity model in response to modeling errors and disturbances, hence producing a reliable viscosity estimate. The experimental results on different material/die/extruder confirm the effectiveness of the proposed “soft sensor” method based on dynamic gray-box modeling for real-time monitoring and control of polymer extrusion processes. POLYM. ENG. SCI., 2012. © 2012 Society of Plastics Engineers
Original languageEnglish
Pages (from-to)1332-1341
JournalPolymer Engineering & Science
Issue number6
Early online date15 May 2012
Publication statusPublished - Jun 2012

ASJC Scopus subject areas

  • Polymers and Plastics
  • Materials Chemistry
  • Chemistry(all)


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