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A One-Class-Based Supervision System to Detect Unexpected Events in Wastewater Treatment Plants
- Source :
- Applied Sciences, Vol 14, Iss 12, p 5185 (2024)
- Publication Year :
- 2024
- Publisher :
- MDPI AG, 2024.
-
Abstract
- The increasing importance of water quality has led to optimizing the operation of Wastewater Treatment Plants. This implies the monitoring of many parameters that measure aspects such as solid suspension, conductivity, or chemical components, among others. This paper proposes the use of one-class algorithms to learn the normal behavior of a Wastewater Treatment Plants and detect situations in which the crucial parameters of Chemical Oxygen Demand, Ammonia, and Kjeldahl Nitrogen present unexpected deviations. The classifiers are tested using different deviations, achieving successful results. The final supervision systems are capable of detecting critical situation, contributing to decision-making and maintenance effectiveness.
Details
- Language :
- English
- ISSN :
- 20763417
- Volume :
- 14
- Issue :
- 12
- Database :
- Directory of Open Access Journals
- Journal :
- Applied Sciences
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.06ce86b0be394c568046a36e83855d0e
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/app14125185