Robust sensing suite for measuring temporal dynamics of surface temperature in sewers

Abstract

Sewerage systems are paramount underground infrastructure assets for any nation. In most cities, they are old and have been exposed to significant microbial induced corrosion. It is a serious global problem as they pose threats to public health and economic repercussions to water utilities. For managing sewer assets efficaciously, it is vital to predict the rate of corrosion. Predictive models of sewer corrosion incorporate concrete surface temperature measurements as an observation. However, currently, it has not been fully utilized due to unavailability of a proven sensor. This study reports the feasibility of infrared radiometer for measuring the surface temperature dynamics in the aggressive sewer conditions. The infrared sensor was comprehensively evaluated in the laboratory at different environmental conditions. Then, the sensor suite was deployed in a Sydney based sewer for three months to perform continuous measurements of surface temperature variations. The field study revealed the suitability of the developed sensor suite for non-contact surface temperature measurements in hostile sewer conditions. Further, the accuracy of the sensor measurements was improved by calibrating the sensor with emissivity coefficient of the sewer concrete. Overall, this study will ameliorate the present sewer corrosion monitoring capabilities by providing new data to models predicting sewer corrosion.

Design and Development of Drill-Resistance Sensor Technology for Accurately Measuring Microbiologically Corroded Concrete Depths

“…Besides direct measurements, predictive models have been developed for estimating the corrosion throughout the sewer network. Quality of such model prediction rely on the data supplies by the sensors [21,22,23,24].…”

A Temporal Forecasting Driven Approach Using Facebook’s Prophet Method for Anomaly Detection in Sewer Air Temperature Sensor System

“…Those models primarily incorporate air temperature, relative humidity, and hydrogen sulphide concentration of sewer air as data inputs to the model [14]. Also, the model takes surface temperature sensor measurements [15], [16] and surface moisture sensor measurements [17]- [19] as additional inputs to reduce prediction uncertainty. This predictive analytics based corrosion estimation needs longterm sensor inputs.…”

“…The sensor was deployed on 3 rd November 2016. The readers are suggested to refer [15] for more details on sensor deployment. This paper proposes a temporal forecasting driven approach for anomaly detection in sewer air temperature sensor system.…”

Short-term Time Series Forecasting of Concrete Sewer Pipe Surface Temperature

“…The predictive performance of the model can be improved in areas where there is low confidence in estimating corrosion by supplying concrete surface temperature and moisture conditions as data inputs to the model [8]- [13]. Recently, a robust sensing suite for monitoring the temporal variations of concrete surface temperature conditions was developed [14]. The data inputs from this sensor are crucial for accurate sewer pipe corrosion prediction.…”