Abstract
Online monitoring of wastewater quality parameters is vital for an efficient and stable operation of wastewater treatment plants (WWTP). Several WWTPs rely on daily/weekly analysis of water samples rather than online automated wet-analyzers due to their high capital and maintenance costs. Soft-sensors are emerging as a viable alternative for real-time monitoring of parameters that either lack a reliable measuring principle or are measured using expensive online sensors. This paper presents the development, implementation, and validation of a hybrid soft sensor used to estimate Total Phosphorus (TP) and Chemical Oxygen Demand (COD) in the influent and effluent streams of a full-scale WWTP. A systematic method for cleaning and processing sensor data, identifying statistically significant correlations, and developing a mathematical model, is discussed. A non-intrusive Industrial Internet of Things (IIoT) infrastructure for soft-sensor deployment and a web-based GUI for data visualization are also presented in this work. The values of TP and COD estimated by the soft sensor are validated by comparing the estimated values to the daily average of their corresponding lab measurements. The data validation results demonstrate the potential of soft sensors in providing real-time values of essential wastewater quality parameters with an acceptable degree of accuracy.
Highlights
The chemical wastewater treatment process, which includes coagulation and flocculation followed by sedimentation, is one of the most commonly used wastewater treatment processes in Norway [1]
The secure, non-intrusive, cost-effective system enables the codes written in scientific programming languages such as Python to be deployed for real-time estimation
The results presented in this work demonstrates that Multiple Linear Regression (MLR) models can be used to develop statistically significant correlations between online sensor data and wastewater quality parameters such as Total Phosphorus (TP) and Chemical Oxygen Demand (COD)
Summary
The chemical wastewater treatment process, which includes coagulation and flocculation followed by sedimentation, is one of the most commonly used wastewater treatment processes in Norway [1]. The operational efficiency of Wastewater Treatment Plants (WWTPs) based on chemical treatment is maintained by ensuring an optimal dosage of coagulants and flocculants. Several control strategies varying from simple flow proportional to sophisticated multi-parameter-based dosing control strategies [2] can be found in the literature. The growing number of users of the multi-parameter-based dosing control strategies provide impetus to monitor additional wastewater quality parameters in WWTPs. WWTPs use several methods to monitor essential wastewater quality parameters. WWTPs use several methods to monitor essential wastewater quality parameters These methods vary from the offline analysis of water samples using standardized lab tests [3] to online sensors that can relay real-time data to the Supervisory Control And
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
