Beyond signal quality: The value of unmaintained pH, dissolved oxygen, and oxidation-reduction potential sensors for remote performance monitoring of on-site sequencing batch reactors
| Autor: | Kris Villez, Mariane Yvonne Schneider, Juan Pablo Carbajal, Bettina Sterkele, Max Maurer, Viviane Furrer |
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| Rok vydání: | 2018 |
| Předmět: |
Environmental Engineering
bepress|Engineering|Civil and Environmental Engineering|Environmental Engineering bepress|Engineering 0208 environmental biotechnology Sequencing batch reactor 02 engineering and technology 010501 environmental sciences 01 natural sciences Waste Disposal Fluid Bioreactors Reduction potential Signal quality engrXiv|Engineering|Civil and Environmental Engineering Process engineering Waste Management and Disposal 0105 earth and related environmental sciences Water Science and Technology Civil and Structural Engineering engrXiv|Engineering|Civil and Environmental Engineering|Environmental Engineering business.industry Ecological Modeling Reproducibility of Results Hydrogen-Ion Concentration Soft sensor Pollution 020801 environmental engineering Oxygen engrXiv|Engineering bepress|Engineering|Civil and Environmental Engineering Nitrite oxidation Detection performance Environmental science Performance monitoring Aeration rate business Oxidation-Reduction |
| Popis: | Sensor maintenance is time-consuming and is a bottleneck for monitoring on-site wastewater treatment systems. Hence, we compare maintained and unmaintained sensors to monitor the biological performance of a small-scale sequencing batch reactor (SBR). The sensor types are ion-selective pH, optical dissolved oxygen (DO), and oxidation-reduction potential (ORP) with platinum electrode. We created soft sensors using engineered features: ammonium valley for pH, oxidation ramp for DO, and nitrite ramp for the ORP. Four soft sensors based on unmaintained pH sensors correctly identified the completion of the ammonium oxidation (89-91 out of 107 cycles), about as many times as soft sensors based on a maintained pH sensor (91 out of 107 cycles). In contrast, the DO soft sensor using data from a maintained sensor showed slightly better (89 out of 96 cycles) detection performance than that using data from two unmaintained sensors (77, respectively 82 out of 96 correct). Furthermore, the DO soft sensor using maintained data is much less sensitive to the optimisation of cut-off frequency and slope tolerance than the soft sensor using unmaintained data. The nitrite ramp provided no useful information on the state of nitrite oxidation, so no comparison of maintained and unmaintained ORP sensors was possible in this case. We identified two hurdles when designing soft sensors for unmaintained sensors: i) Sensors' type- and design-specific deterioration affects performance. ii) Feature engineering for soft sensors is sensor type specific, and the outcome is strongly influenced by operational parameters such as the aeration rate. In summary, the results with the provided soft sensors show that frequent sensor maintenance is not necessarily needed to monitor the performance of SBRs. Without sensor maintenance monitoring small-scale SBRs becomes practicable, which could improve the reliability of unstaffed on-site treatment systems substantially. |
| Databáze: | OpenAIRE |
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