Abstract

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.

Highlights

  • Small scale on-site wastewater treatment (OST) plants are capable of achieving the relative performance of large-scale wastewater treatment plants (WWTP) (e.g. Abegglen and Siegrist, 2006)

  • Four soft sensors based on unmaintained pH sensors correctly 23 identified the completion of the ammonium oxidation (89 to 91 out of 107 cycles), about 24 as many times as soft sensors based on a maintained pH sensor (91 out of 107 cycles)

  • 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

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Summary

Introduction

Small scale on-site wastewater treatment (OST) plants are capable of achieving the relative performance of large-scale wastewater treatment plants (WWTP) (e.g. Abegglen and Siegrist, 2006). Small scale on-site wastewater treatment (OST) plants are capable of achieving the relative performance of large-scale wastewater treatment plants (WWTP) A system of OST plants with adequate monitoring and associated demand-driven maintenance scheme might be able to deliver performance on par with a single centralised plant (Eggimann et al, 2017). Like Germany, OST are inspected two to three times per year (DIBt, 2012) and many undetected failures of the plants occur (Moelants et al, 2008). A change towards decentralised treatment requires solutions for monitoring the performance of OST systems

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