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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Li, Kang
University of Leeds
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (9/9 displayed)
- 2016Use of a ceramic membrane to improve the performance of two-separate-phase biocatalytic membrane reactorcitations
- 2014Investigation of the temperature homogeneity of die melt flows in polymer extrusioncitations
- 2014Process efficiency in polymer extrusion: Correlation between the energy demand and melt thermal stabilitycitations
- 2014Energy monitoring and quality control of a single screw extrudercitations
- 2014Investigation of the process energy demand in polymer extrusion: a brief review and an experimental studycitations
- 2014Low-cost Process monitoring for polymer extrusion
- 2012Dynamic grey-box modeling for online monitoring of extrusion viscositycitations
- 2011The inferential monitoring of screw load torque to predict process fluctuations in polymer extrusioncitations
- 2011The inferential monitoring of the screw disturbance torque to predict process fluctuations in polymer extrusioncitations
Places of action
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article
Dynamic grey-box modeling for online monitoring of extrusion viscosity
Abstract
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