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Data-derived soft-sensors for biological wastewater treatment plants: An overview
Affiliation:1. Department of Chemical Engineering, McMaster University 1280 Main Street West, Hamilton, Ontario, L8S 4L8, Canada;7. Analytical Technology Center, The DOW Chemical Company 2301 Brazosport Blvd., Freeport, TX 77541, USA
Abstract:This paper surveys and discusses the application of data-derived soft-sensing techniques in biological wastewater treatment plants. Emphasis is given to an extensive overview of the current status and to the specific challenges and potential that allow for an effective application of these soft-sensors in full-scale scenarios. The soft-sensors presented in the case studies have been found to be effective and inexpensive technologies for extracting and modelling relevant process information directly from the process and laboratory data routinely acquired in biological wastewater treatment facilities. The extracted information is in the form of timely analysis of hard-to-measure primary process variables and process diagnostics that characterize the operation of the plants and their instrumentation. The information is invaluable for an effective utilization of advanced control and optimization strategies.
Keywords:Water quality monitoring  Soft-sensors  Data-driven models  Wastewater treatment
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