Background: The main goal of wastewater treatment is to obtain high quality effluent. This study proposes a methodology to estimate in real-time the effluent quality in a biological nutrient removal (BNR) sequencing batch reactor (SBR) process. Results: This is achieved by: (i) detecting the batch quality; and (ii) predicting the classification of the release according to different effluent characteristics. A principal component analysis (PCA) model is built to discern normal or abnormal behavior of the batch release. An index is given to every phase of the process by means of contribution analysis, and a fault signature (FS) is created. The FS in a classification model is associated with a biological removal quality. Conclusion: The model is applied as a soft-sensor in real-time to new batch releases to obtain a qualitative estimate of the effluent. A correct estimation for the qualitative variables, of above 95%, would provide a reliable tool to estimate BNR performances.
ASJC Scopus subject areas
- Inorganic Chemistry
- Waste Management and Disposal
- Organic Chemistry
- Renewable Energy, Sustainability and the Environment
- Chemical Engineering(all)
- Fuel Technology