Water pipeline failure detection using distributed relative pressure and temperature measurements and anomaly detection algorithms

Abstract

This paper presents the validation of a novel leak detection method for water distribution pipelines, although it could be applied to any buried pressurized fluid flow pipe. The detection method is based on a relative pressure sensor attached non-invasively to the outside of the pipe combined with temperature difference measurements between the pipe wall and the soil. Moreover, this paper proposes an anomaly detection algorithm, originally developed for monitoring website traffic data, which differentiates a 'leak' event from 'normal' pressure change events. It is compared to two more commonly used methods based on a fixed threshold and a moving average. The validation of the new system in a field trial over a 6-month period showed that all the known leaks were identified with 98.45% accuracy, with the anomaly detection algorithm performing best, making this system a real contender for leak detection in pipes.

Time domain reflectometry (TDR) potential for soil condition monitoring of geotechnical assets

“…8a) and based on the large and sudden change of S r (expressed by its first derivative, Fig. 8c), which can be identified visually by applying a specific threshold or by using change detection algorithms (e.g., Sadeghioon et al 2018; change detection algorithms are not discussed here as they are out of the scope of this paper). The absolute values of S r (Fig.…”

A Review of the Real-Time Monitoring of Fluid-Properties in Tubular Architectures for Industrial Applications

“…A network of distributed pressure sensors and thermometers on the external pipe walls can detect pipe failures. The study [ 34 ] presents a relative temperature difference between the pipe wall and the soil at each node from the distributed sensors, where it indicates the unexpected change in the fluid flow rate leading to leaking detection. In addition, each node includes a pressure gauge to detect abnormal pressure drop to support the detection results.…”

Detección de fallos en redes de presión pertenecientes a redes de suministro de agua mediante filtros estáticos lineales basados en PCA

“…Los errores más grandes los proporcionan los nodos [15,12,8] (ver Tabla 1) y por tanto serán los que conformen la base principal. Mediante el algoritmo expuesto en la Sección 3.1 se calcula también la base secundaria.…”

“…Las redes de sensores subterráneas inalámbricas (WSDN) ofrecen una plataforma muy adaptable para la monitorización de amplias redes de tuberías gracias a su escalabilidad y capacidad de monitorear de manera continuada. Existe una amplia variedad de este tipo de redes [2,19,17,13,5,21,15]. Sin embargo, dichas redes dependen usualmente de sensores de presión que introducen puntos de fuga similares a los de las líneas de servicio [18] o contaminación en los tubos de cemento de asbesto [20].…”