697
Views
14
CrossRef citations to date
0
Altmetric
Research Articles

A methodology for leak detection in water distribution networks using graph theory and artificial neural network

, ORCID Icon &
Pages 525-533 | Received 15 Feb 2020, Accepted 10 Jul 2020, Published online: 05 Aug 2020
 

ABSTRACT

Considering the scarcity of water resources, it is necessary to identify the leakage in Water Distribution Networks (WDNs). In this paper, a step-by-step method of WDN decomposition has been introduced for leak detection. First, the WDN is divided into two parts using the graph theory, then the part with leakage is identified using the results of pressure loggers and the artificial neural network. This process continues for the identified part to reach the limited leakage area. This method was applied to the Balerma WDN with five leakage scenarios including uncertainty of demand and pressure parameters. The results show that the proposed method can find the leakage area of WDNs with good accuracy.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.