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Dynamic gray-box modeling for on-line monitoring of polymer extrusion viscosity

journal contribution
posted on 2023-06-09, 07:14 authored by Xueqin Liu, Kang Li, Marion McAfee, Bao Kha NguyenBao Kha Nguyen, Gerald McNally
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.

History

Publication status

  • Published

Journal

Polymer Engineering and Science

ISSN

0032-3888

Publisher

John Wiley & Sons

Issue

6

Volume

52

Page range

1332-1341

Department affiliated with

  • Engineering and Design Publications

Full text available

  • No

Peer reviewed?

  • Yes

Legacy Posted Date

2017-07-17

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