Integrated Soft-Sensor Model for Wastewater Treatment Process with Collaborative Calibration Strategy

The soft-sensor model (SSM) has been widely used for monitoring water quality, operational state, and performance evaluation in wastewater treatment process (WWTP). However, due to serious dynamics in WWTP under different working conditions, SSM faces a challenge to maintain excellent performance. To address this issue, an integrated soft-sensor model (ISSM) is introduced for WWTP based on a collaborative calibration strategy in this study. Different from the previous studies, the SSM is equipped with the given model structure with respect to certain input variables. The proposed ISSM has the capability of updating its structure online to adapt to the changes in input variables with a structural collaborative calibration strategy. The parameters of ISSM, associated with feature extraction of input variables and feature representation of its input–output, are calibrated simultaneously with a parametric collaborative calibration strategy. As a result, this model can improve its adaptability to the dynamics of WWTP and further maintain the accuracy of real-time monitoring. Finally, the ISSM is used to monitor the total nitrogen removal in WWTP. Its RMSE on the test set is lower than that of most comparison algorithms, with a streamlined network architecture enabling monitoring, which validates its effectiveness and advanced nature.