Work

Hybrid Transient-Machine Learning Methodology for Leak Detection in Water Transmission Mains

Year: 2024

Type: conference-paper

Abstract: This contribution proposes a hybrid approach integrating transient test-based techniques with machine learning for automatic leak detection in water transmission mains. Transient numerical simulations calibrated using experimental tests are used to develop a data-driven method based on neural networks to identify leak locations and characteristics. The accuracy of leak localization is demonstrated using three different degrees of noise in terms of mean absolute error, ranging between 0.54 m and 2.1 m. This proposed hybrid approach shows prospects for in-field applications.

DOI: 10.3390/engproc2024069142

Authors: Caterina Capponi, Andrea Menapace, Silvia Meniconi, Daniele Dalla Torre, Maurizio Tavelli, Maurizio Righetti, Bruno Brunone

Institutions: University of Perugia, Free University of Bozen-Bolzano

Language: English

Topic: Water Systems and Optimization

Subfield: Civil and Structural Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Clean water and sanitation

Open Access status: gold

OpenAlex ID: W4402809957

FWCI:

Cites: 10

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Related to: 10