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

Abstract

Sensor maintenance is time-consuming and is a bottleneck for monitoring on-site wastewater treatment systems. Hence, we compare maintained and unmaintained pH, dissolved oxygen (DO), and oxidation-reduction potential (ORP) sensors to monitor the biological performance of a small-scale sequencing batch reactor (SBR). We created soft sensors using engineered features: ammonium valley for pH, oxidation ramp for DO, and nitrite ramp for the ORP. We found that the pH soft sensors are able to reliably identify the completion of ammonium oxidation in the SBR’s effluent even without sensor maintenance for over a year. In contrast, the DO soft sensor using data from a maintained sensor showed slightly better detection performance than that using data from unmaintained sensors, as 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, we provide soft sensors that allow the performance of unstaffed small-scale SBRs to be monitored with unmaintained sensors and therefore the maintenance and reliability of OST systems to be optimised.