Theoretical Idea for Identification of Leakage Areas in Virtual District Metered Areas of Water Distribution Networks Using the Artificial Neural Network

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Shekofteh M.R.; JALILI GHAZIZADEH M.R.; YAZDI J.

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Journal: IRAN-WATER RESOURCES RESEARCH Year:2020 | Volume:16 | Issue:3 Page(s): 47-62

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Title

Theoretical Idea for Identification of Leakage Areas in Virtual District Metered Areas of Water Distribution Networks Using the Artificial Neural Network

Author(s)

Shekofteh M.R. | JALILI GHAZIZADEH M.R. | YAZDI J. | Issue Writer Certificate

Keywords

LeakageQ2

Graph TheoryQ1

Virtual District Metered AreasQ1

Water Distribution NetworkQ2

Artificial Neural NetworkQ2

Hydraulic SimulationQ1

Abstract

One of the advantages of designing Water Distribution Networks (WDNs) as district metered areas (DMAs) is that the Leakage in each area can be identified by controlling the input and output flow, which of course requires that the areas are separated and flowmeters are installed between the interconnecting pipes of each area. Since most existing WDNs have been expanded traditionally and not as DMA, turning them into DMAs would require huge costs and might not be even practical in some networks. In this paper, the theoretical idea of virtual DMA is presented to identify the Leakage in each areas. The innovation of this paper is the ability to transform networks into DMAs using a combination of the Graph Theory and Artificial Neural Network to find leaks without using a flowmeter. The proposed method, in addition to reducing the costs for the flowmeters, increases the speed of detection of Leakage areas. Furthermore, there is no need to specify the number of Leakage nodes before the leak detection begins. The proposed method has been applied to the Balerma WDN in Spain with 443 nodes and 454 pipes for two, three and four simultaneous leaks. The results of this paper showed that the proposed theory is able to detect Leakage in each area, and this method can determine the number of optimal virtual DMAs for each network. In all examples, the Leakage area was correctly predicted and the maximum Leakage error was about 6. 5%.

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APA: Copy

Shekofteh, M.R., JALILI GHAZIZADEH, M.R., & YAZDI, J.. (2020). Theoretical Idea for Identification of Leakage Areas in Virtual District Metered Areas of Water Distribution Networks Using the Artificial Neural Network. IRAN-WATER RESOURCES RESEARCH, 16(3 ), 47-62. SID. https://sid.ir/paper/407728/en

Vancouver: Copy

Shekofteh M.R., JALILI GHAZIZADEH M.R., YAZDI J.. Theoretical Idea for Identification of Leakage Areas in Virtual District Metered Areas of Water Distribution Networks Using the Artificial Neural Network. IRAN-WATER RESOURCES RESEARCH[Internet]. 2020;16(3 ):47-62. Available from: https://sid.ir/paper/407728/en

IEEE: Copy

M.R. Shekofteh, M.R. JALILI GHAZIZADEH, and J. YAZDI, “Theoretical Idea for Identification of Leakage Areas in Virtual District Metered Areas of Water Distribution Networks Using the Artificial Neural Network,” IRAN-WATER RESOURCES RESEARCH, vol. 16, no. 3 , pp. 47–62, 2020, [Online]. Available: https://sid.ir/paper/407728/en

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