Detection of sludge bulking using adaptive fuzzy neural network and mechanism model

Abstract

The frequent occurrence of sludge bulking can influence the effluent qualities and destroy the stable operation of activated sludge process (ASP). In order to accurately detect the sludge bulking, a detection method, based on adaptive fuzzy neural network and mechanism model, is proposed in this paper. First, a novel detection scheme is designed, where hybrid detection model and intelligent identification algorithm, are designed to describe the dynamics of sludge bulking. Second, an error compensation model, by using adaptive fuzzy neural network, is established to make up for the errors caused by the assumptions set in hybrid detection model. Finally, an error-assisted detection strategy is designed to evaluate sludge bulking. To verify the effectiveness of the proposed detection method, operating data from ASP are applied. The results show that this proposed method can efficiently detect sludge bulking.