Leak signature space: an original representation for robust leak location in water distribution networks
In this paper, an original model-based scheme for leak location using pressure sensors in water distribution networks is introduced. The proposed approach is based on a new representation called the Leak Signature Space (LSS) that associates a specific signature to each leak location being minimally...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2015 |
| 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:2117/27696 |
| Acceso en línea: | https://hdl.handle.net/2117/27696 https://dx.doi.org/10.3390/w7031129 |
| Access Level: | acceso abierto |
| Palabra clave: | Water-supply pipe networks sensor diagnosis algorithm systems water distribution networks leak location linear model approximation leak signature space Aigua -- Abastament Àrees temàtiques de la UPC::Enginyeria civil::Enginyeria hidràulica, marítima i sanitària |
| Sumario: | In this paper, an original model-based scheme for leak location using pressure sensors in water distribution networks is introduced. The proposed approach is based on a new representation called the Leak Signature Space (LSS) that associates a specific signature to each leak location being minimally affected by leak magnitude. The LSS considers a linear model approximation of the relation between pressure residuals and leaks that is projected onto a selected hyperplane. This new approach allows to infer the location of a given leak by comparing the position of its signature with other leak signatures. Moreover, two ways of improving the method's robustness are proposed. First, by associating a domain of influence to each signature and second, through a time horizon analysis. The efficiency of the method is highlighted by means of a real network using several scenarios involving different number of sensors and considering the presence of noise in the measurements. |
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