A distributed analysis of vibration signals for leakage detection in Water Distribution Networks

A distributed analysis of vibration signals for leakage detection in Water Distribution Networks

Gabriele Restuccia, Ilenia Tinnirello, Fulvio Lo Valvo, Giacomo Baiamonte, Domenico Garlisi, Costantino Giaconia

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Abstract. It is well known that Water Distribution Networks (WDNs) are very inefficient and, in Italy, 40% of water is lost during distribution. In this paper, we present a solution for detecting leakages in WDNs, based on three main components: i) an innovative sensing element to be deployed at the sensor nodes, which analyses vibrations in the acoustic range for classifying external noise sources, induced by water leakages, by means of suitable machine learning techniques; ii) an Internet of Things (IoT) system of sensors, deployed at the junctions of the WDNs, for comparing the measurements collected at different critical points of the network; iii) a machine learning algorithm for processing the data. After the definition of the WDN structure, we introduce some numerical simulation tools suitable for studying our system and modeling the proposed sensing solution. Given the geometry, physical properties (pipe lengths, diameters, roughness, reservoir shapes and levels, pump and valve characteristic curves) and nodal demands, the simulation tool is able to compute leakages in pipes or nodes over time. In parallel, we simulate our IoT system coupled to the WDN, by logging partial information about the WDN status, which corresponds to the demand readings at the edge nodes or at some junction nodes, together with the (optional) measurements of the deployed sensing elements. On the basis of this data, we analyze the possibility of identifying the leakages in the network, even without knowing the exact or complete topology of the WDN. Our solution exploits different machine learning techniques devised to indirectly retrieve topological information, by correlating the balance of the flows as the water demand varies over time.

Smart Water Distribution Network (SWDN), LoRaWAN, Vibrations Sensor

Published online 3/17/2022, 6 pages
Copyright © 2023 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA

Citation: Gabriele Restuccia, Ilenia Tinnirello, Fulvio Lo Valvo, Giacomo Baiamonte, Domenico Garlisi, Costantino Giaconia, A distributed analysis of vibration signals for leakage detection in Water Distribution Networks, Materials Research Proceedings, Vol. 26, pp 543-548, 2023

DOI: https://doi.org/10.21741/9781644902431-88

The article was published as article 88 of the book Theoretical and Applied Mechanics

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

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