A chemometric approach to prediction of transmembrane pressure in membrane bioreactors
Membrane bioreactors (MBRs) have been widely used to purify wastewater for reuse. However, MBRs are subject to fouling, which is the phenomenon whereby foulants absorb or deposit on the membrane. To enable chemical cleaning to be performed at an appropriate time, membrane fouling must to be predicted in the long term. There has been research on correlations among fouling phenomena, water quality variables, and operating conditions. Therefore, in this paper, we aimed to construct a chemometric or statistical model between the increase in the transmembrane pressure (TMP) and MBR parameters such as water quality variables and operating conditions and use this model to predict IMP. We analyzed three data sets measured in real industrial MBR plants and then confirmed that the constructed model could predict TMP over time with high accuracy. By applying the proposed method to process control, MBR plants will be operated effectively and stably. (C) 2013 Elsevier B.V. All rights reserved.
chemometrics membrane bioreactor water quality operating conditions fouling prediction soft sensor