On-line estimation and detection of abnormal substrate concentrations in WWTPs using a software sensor: A benchmark study

In this paper, a new approach for on-line monitoring and detection of abnormal readily biodegradable substrate (SS) and slowly biodegradable substrate (XS) concentrations, for example due to input of toxic loads from the sewer, or due to influent substrate shock load, is proposed. Considering that measurements of SS and XS concentrations are not available in real wastewater treatment plants, the SS | XS software sensor can activate an alarm with a response time of about 60 and 90 minutes, respectively, based on the dissolved oxygen measurement. The software sensor implementation is based on an extended Kalman filter observer and disturbances are modelled using fast Fourier transform and spectrum analyses. Three case studies are described. The first one illustrates the fast and accurate convergence of the extended Kalman filter algorithm, which is achieved in less than 2 hours. Furthermore, the difficulties of estimating XS when off-line analysis is not available are depicted, and the SS | XS software sensor performances when no measurements of SS and XS are available are illustrated. Estimation problems related to the death-regeneration concept of the activated sludge model no.1 and possible application of the software sensor in wastewater monitoring are discussed.