Abstract
It is one of the important issues in the field of today's sewage treatment of researching the MBR membrane flux prediction for membrane fouling. Firstly this paper used the principal component analysis method to achieve dimensionality and correlation of input variables and obtained the three major factors affecting membrane fouling most obvious: MLSS, total resistance, and operating pressure. Then it used the BP neural network to establish the system model of the MBR intelligent simulation, the relationship between three parameters, and membrane flux characterization of the degree of membrane fouling, because the BP neural network has slow training speed, is sensitive to the initial weights and the threshold, is easy to fall into local minimum points, and so on. So this paper used genetic algorithm to optimize the initial weights and the threshold of BP neural network and established the membrane fouling prediction model based on GA-BP network. As this research had shown, under the same conditions, the BP network model optimized by GA of MBR membrane fouling is better than that not optimized for prediction effect of membrane flux. It demonstrates that the GA-BP network model of MBR membrane fouling is more suitable for simulation of MBR membrane fouling process, comparing with the BP network.
Highlights
As a new wastewater treatment technology, the membrane bioreactor has attracted much concern by its high quality of the effluent water quality and was considered as a watersaving technology with better economic, social, and environmental benefits
For MBR membrane fouling factor, the traditional mathematical model of MBR membrane fouling has some defects in different degrees, which cannot accurately explain the phenomenon of membrane fouling; this paper introduced some intelligent algorithms by consulting relevant references, such as neural network and genetic algorithm, to build the model of MBR membrane fouling and implement relevant optimization
We established the system model of MBR intelligent simulation based on BP neural network, about the relationship between the membrane fouling factors and membrane fouling that expresses the degree of membrane flux
Summary
As a new wastewater treatment technology, the membrane bioreactor has attracted much concern by its high quality of the effluent water quality and was considered as a watersaving technology with better economic, social, and environmental benefits. The MBR computer simulation technology has become a powerful tool for the research of the MBR, and its development will have a positive reference and guiding role for the practical engineering applications of the MBR Based on this idea, according to the real data of the experiment and industrial production of a MBR sewage treatment plant in Shijiazhuang, this paper focused on membrane fouling problem in the process of membrane bioreactor sewage wastewater. Seeking the optimum operating conditions of controlling membrane pollution trend, it improved the membrane fouling problem of the MBR process The research of this topic had a certain reference value for membrane fouling prediction, parameters selection, and operation of the MBR practical engineering. Abstract and Applied Analysis and further expressed technological advantages of this process
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