Author(s): Anastasios Perdios; George Kokosalakis; Nikolaos Th. Fourniotis; Irene Karathanasi; Andreas Langousis

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Abstract: Pressure reducing valves (PRVs) are widely used to regulate pressures in the supply and distribution parts of water networks, by reducing the upstream pressure to a set outlet pressure (i. e., downstream of the PRV), usually referred to as set point. As all types of mechanical equipment, PRVs may exhibit malfunctions affecting pressure regulation, such as high frequency fluctuations around the set point and/or prolonged systematic deviations from the set point, allowing their detection to be approached in a statistical context. This work focuses on the implementation of a novel statistical framework (see Perdios et al., 2022) to an existing pressure management area (PMA) of the city of Patras in western Greece, aiming at early detection of PRV malfunctions. The implemented framework uses: a) the cumulative distribution function (CDF) of the root mean squared error (RMSE) to monitor the performance of PRVs by detecting individual malfunctions, and b) the hazard function concept to identify a proper duration of sequential events from (a) to issue alerts.

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Year: 2022