Soft-sensor Method for Permeability of the Membrane Bio-Reactor Based on Recurrent Radial Basis Function Neural Network

A soft-sensor method, based on the recurrent radial basis function neural network (RRBFNN), was proposed in this paper to solve the problem of the permeability measurement of membrane bio-reactor (MBR). First, the data was collected from a real wastewater treatment process in Beijing and the partial least squares (PLS) technique was utilized to select the variables which have the largest correlation with the permeability. Then, the soft-sensor model was developed to predict the permeability via RRBFNN. Meanwhile, a fast gradient descent method was used to adjust the parameters of RRBFNN. Finally, this soft-sensor method was applied to the real wastewater treatment process. The results show that the proposed soft-sensor method can predict the permeability of MBR with high accuracy.