Towards intelligent ultrafiltration

Towards intelligent ultrafiltration

To better control fouling of ultrafiltration membranes, data mining techniques can be applied on everyday plant measurements to deduce the current fouling state of the membranes. In this project, principal component analysis (PCA) is applied to transmembrane pressure (TMP) data to characterise the severity as well as nature (reversible or irreversible) of the fouling. Temperature dependency is evaluated as well as correlation with other process parameters.

Project duration: 2013-05-01 - 2014-04-30

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Thomas Maere
Department of Applied Mathematics, Biometrics and Process Control
Coupure Links 653
9000 Gent

Tel: +32 (0)9 264 5937

Last update: 01 december 2008,

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