Multivariable identification of membrane fouling based on compacted cascade neural network

The system consists of three modules: data acquisition, feature extraction, and online prediction. The data acquisition module obtains the value of process variables from the sensor and transfers the acquired variables to the database via PLC. The feature extraction module is designed to filter the collected process data. In this module, multiple related variables are selected as the preselected variables. Then the PLS method is used to reduce the dimension of the preselected variables to obtain the feature variables with a high correlation with the predicted variables. Finally, the online prediction module based on a cascade neural network predicts membrane fouling, membrane integrity, and membrane life for clean decisions.