An approach based on hydraulic simulation and machine learning is presented, aimed at improving leakage management via analytical leak localization and reducing time and costs for investigation and rehabilitation of the Water Distribution Network. Hydraulic simulation is used to run different leakage scenarios by introducing a leak on each pipe, in turn, and varying its severity. The approach has been validated on two WDNs: a Pressure Management Zone in Milan (Italy) and a District Metered Area in Timisoara (Romania), the two pilots of the EU-FP7-ICT project ICeWater, obtaining a high reliability (>90%) in localizing a wide set of simulated leaks
Candelieri, A., Soldi, D., Conti, D., Archetti, F. (2014). Analytical Leakages Localization in Water Distribution Networks through Spectral Clustering and Support Vector MACHINES. The Icewater Approach. PROCEDIA ENGINEERING, 89, 1080-1088 [10.1016/j.proeng.2014.11.228].
Analytical Leakages Localization in Water Distribution Networks through Spectral Clustering and Support Vector MACHINES. The Icewater Approach
Candelieri, A;Archetti, FA
2014
Abstract
An approach based on hydraulic simulation and machine learning is presented, aimed at improving leakage management via analytical leak localization and reducing time and costs for investigation and rehabilitation of the Water Distribution Network. Hydraulic simulation is used to run different leakage scenarios by introducing a leak on each pipe, in turn, and varying its severity. The approach has been validated on two WDNs: a Pressure Management Zone in Milan (Italy) and a District Metered Area in Timisoara (Romania), the two pilots of the EU-FP7-ICT project ICeWater, obtaining a high reliability (>90%) in localizing a wide set of simulated leaksFile | Dimensione | Formato | |
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