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Leak Localization in Water Distribution Networks Using Data-Driven and Model-Based Approaches
https://orcid.org/0000-0002-4790-2031
https://orcid.org/0000-0002-5626-3753
https://orcid.org/0000-0002-1622-0994
The detection and localization of leaks in water distribution networks (WDNs) is one of the major concerns of water utilities, due to the necessity of an efficient operation that satisfies the worldwide growing demand for water. There exists a wide range of methods, from equipment-based techniques that rely only on hardware devices to software-based methods that exploit models and algorithms as well. Model-based approaches provide an effective performance but rely on the availability of an hydraulic model of the WDN, while data-driven techniques only require measurements from the network operation but may produce less accurate results. This paper proposes two methodologies: a model-based approach that uses the hydraulic model of the network, as well as pressure and demand information; and a fully data-driven method based on graph interpolation and a new candidate selection criteria. Their complementary application was successfully applied to the Battle of the Leakage Detection and Isolation Methods (BattLeDIM) 2020 challenge, and the achieved results are presented in this paper to demonstrate the suitability of the methods.
Leak Localization in Water Distribution Networks Using Data-Driven and Model-Based Approaches
https://orcid.org/0000-0002-4790-2031
https://orcid.org/0000-0002-5626-3753
https://orcid.org/0000-0002-1622-0994
The detection and localization of leaks in water distribution networks (WDNs) is one of the major concerns of water utilities, due to the necessity of an efficient operation that satisfies the worldwide growing demand for water. There exists a wide range of methods, from equipment-based techniques that rely only on hardware devices to software-based methods that exploit models and algorithms as well. Model-based approaches provide an effective performance but rely on the availability of an hydraulic model of the WDN, while data-driven techniques only require measurements from the network operation but may produce less accurate results. This paper proposes two methodologies: a model-based approach that uses the hydraulic model of the network, as well as pressure and demand information; and a fully data-driven method based on graph interpolation and a new candidate selection criteria. Their complementary application was successfully applied to the Battle of the Leakage Detection and Isolation Methods (BattLeDIM) 2020 challenge, and the achieved results are presented in this paper to demonstrate the suitability of the methods.
Leak Localization in Water Distribution Networks Using Data-Driven and Model-Based Approaches
https://orcid.org/0000-0002-4790-2031
https://orcid.org/0000-0002-5626-3753
https://orcid.org/0000-0002-1622-0994
The detection and localization of leaks in water distribution networks (WDNs) is one of the major concerns of water utilities, due to the necessity of an efficient operation that satisfies the worldwide growing demand for water. There exists a wide range of methods, from equipment-based techniques that rely only on hardware devices to software-based methods that exploit models and algorithms as well. Model-based approaches provide an effective performance but rely on the availability of an hydraulic model of the WDN, while data-driven techniques only require measurements from the network operation but may produce less accurate results. This paper proposes two methodologies: a model-based approach that uses the hydraulic model of the network, as well as pressure and demand information; and a fully data-driven method based on graph interpolation and a new candidate selection criteria. Their complementary application was successfully applied to the Battle of the Leakage Detection and Isolation Methods (BattLeDIM) 2020 challenge, and the achieved results are presented in this paper to demonstrate the suitability of the methods.
Leak Localization in Water Distribution Networks Using Data-Driven and Model-Based Approaches
J. Water Resour. Plann. Manage.
Romero-Ben, Luis (Autor:in) / Alves, Débora (Autor:in) / Blesa, Joaquim (Autor:in) / Cembrano, Gabriela (Autor:in) / Puig, Vicenç (Autor:in) / Duviella, Eric (Autor:in)
01.05.2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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