Evolving fuzzy model in fault detection system

Abstract

Evolving methods for on-line learning of nonlinear models can play an important role in future monitoring and fault detection systems. The ability to model nonlinear relationships between the measured variables and to adapt the model to changing variable relations can decrease the number of false alarms and ensure a more robust and stable monitoring system. In this paper an example of the waste water treatment process monitoring system based on evolving fuzzy model is presented.