The Study of Membrane Fouling Modeling Method Based on Fuzzy Neural Network for Sewage Treatment Membrane Bioreactor

The membrane bioreactor (MBR) is a new technology of sewage treatment combining the membrane with the bioreactor, but the membrane fouling is an important factor to limit the MBR further development. Considering the issues that the relationship between the membrane fouling and affecting factors is a complicated and nonlinear, a modeling method based on fuzzy neural network is presented in this paper. We construct the structure of fuzzy neural network that used for membrane fouling, and adopt the Levenberg-Marquart optimizing algorithm to train fuzzy neural network. The main parameters of affecting MBR membrane fouling are studied. With the ability of strong self-learning and function approach of fuzzy neural network, the modeling method can detect and assess the membrane fouling degree of MBR in real time by learning the membrane fouling information. The detection results show that this method is feasible and effective.

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