Adaptive data-derived anomaly detection in the activated sludge process of a large-scale wastewater treatment plant

This work examines real-time anomaly detection and isolation in a full-scale wastewater treatment plant: the Viikinmäki plant, which is the largest municipal wastewater treatment facility in Finland. It is monitored with ample instrumentation, though their potential is not yet fully exploited. The methodology is based on principal component analysis.The results show that both instrument and process anomalies were successfully detected using the proposed algorithm and the variables responsible for the anomalies correctly isolated.We also demonstrate that the proposed algorithm represents a convenient improvement for supporting the efficient operation of wastewater treatment plants.