Abstract
Increasing demands on effluent quality and loads call for an improved control, monitoring, and fault detection of waste-water treatment plants (WWTPs). Improved control and optimization of WWTP lead to increased pollutant removal, a reduced need for chemicals as well as energy savings. An important step toward the optimal functioning of a WWTP is to minimize the influence of sensor faults on the control quality. To achieve this, a fault-detection system should be implemented. In this paper, the idea of using an evolving method as a base for the fault-detection/monitoring system is tested. The system is based on the evolving fuzzy model method. This method allows us to model the nonlinear relations between the variables with the Takagi–Sugeno fuzzy model. The method uses basic evolving mechanisms to add and remove clusters and the adaptation mechanism to adapt the clusters’ and local models’ parameters. The proposed fault-detection system is tested on measured data from a real WWTP. The results indicate the potential improvement of the WWTP's control during a sensor malfunction.
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