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Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning
Abstract
The paper presented the methodology for the construction of a soft sensor used for activated sludge bulking identification. Devising such solutions fits within the current trends and development of a smart system and infrastructure within smart cities. In order to optimize the selection of the data-mining method depending on the data collected within a wastewater treatment plant (WWTP), a number of methods were considered, including: artificial neural networks, support vector machines, random forests, boosted trees, and logistic regression. The analysis conducted sought the combinations of independent variables for which the devised soft sensor is characterized with high accuracy and at a relatively low cost of determination. With the measurement results pertaining to the quantity and quality of wastewater as well as the temperature in the activated sludge chambers, a good fit can be achieved with the boosted trees method. In order to simplify the selection of an optimal method for the identification of activated sludge bulking depending on the model requirements and the data collected within the WWTP, an original system of weight estimation was proposed, enabling a reduction in the number of independent variables in a model— quantity and quality of wastewater, operational parameters, and the cost of conducting measurements.
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Authors (6)
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Bartosz Szeląg
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Grzegorz Łagód Dr inż.
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Dariusz Majerek
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Ewa Dacewicz
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Francesco Fatone
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Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
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SENSORS
no. 20,
ISSN: 1424-8220 - Language:
- English
- Publication year:
- 2020
- Bibliographic description:
- Szeląg B., Drewnowski J., Łagód G., Majerek D., Dacewicz E., Fatone F.: Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning// SENSORS -Vol. 20,iss. 7 (2020), s.1941-
- DOI:
- Digital Object Identifier (open in new tab) 10.3390/s20071941
- Sources of funding:
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- This work was financially supported by National Science Centre as a result of the research project no. 2017/26/D/ST8/00967 and Ministry of Science and Higher Education in Poland, within the statutory research of particular scientific units under subvention for a science program.
- Verified by:
- Gdańsk University of Technology
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