Data-driven leak localization in WDN using pressure sensor and hydraulic information
Maintaining a good quality of service under a wide range of operational management is challenging for water utilities. One of the significant challenges is the location of water leaks in the large-scale water distribution networks (WDN) due to limited data information throughout the system, generall...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/381338 |
| Acceso en línea: | https://hdl.handle.net/2117/381338 https://dx.doi.org/10.1016/j.ifacol.2022.07.646 |
| Access Level: | acceso abierto |
| Palabra clave: | Leak detectors Water -- Distribution Water distribution network Flow analysis Pressure analysis Graph theory Data models Detectors de fuites Aigua -- Distribució Àrees temàtiques de la UPC::Informàtica::Automàtica i control |
| Sumario: | Maintaining a good quality of service under a wide range of operational management is challenging for water utilities. One of the significant challenges is the location of water leaks in the large-scale water distribution networks (WDN) due to limited data information throughout the system, generally having only flow sensors at the system's entrance and some pressure sensors in some selected nodes. In addition, most systems do not have a network hydraulic model. Therefore, when using the hydraulic model, the presence of model errors, such as nodal demand uncertainty and measurement noise, can interfere with the performance of the leak location method. This work presents a fully data-driven technique to reduce the area of the leak localization in the WDN, using Graph theory to represent the network. To do so, we have developed distance clustering with pre-defined centroids that are the sensor pressure information and some selected nodes. Furthermore, extra pressure information of leak events in the selected centroids is studied to develop a correlation between the pressure measurement and the event. Finally, the approach is evaluated in real-world water systems and discusses graphical results and key performance indicators. |
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