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Authors: Robert Müller 1 ; Steffen Illium 1 ; Fabian Ritz 1 ; Tobias Schröder 2 ; Christian Platschek 2 ; Jörg Ochs 2 and Claudia Linnhoff-Popien 1

Affiliations: 1 Mobile and Distributed Systems Group, LMU Munich, Germany ; 2 Stadtwerke München GmbH, Germany

Keyword(s): Leak Detection, Water Networks, Acoustic Anomaly Detection, Applied Machine Learning.

Abstract: In this work, we present a general procedure for acoustic leak detection in water networks that satisfies multiple real-world constraints such as energy efficiency and ease of deployment. Based on recordings from seven contact microphones attached to the water supply network of a municipal suburb, we trained several shallow and deep anomaly detection models. Inspired by how human experts detect leaks using electronic sounding-sticks, we use these models to repeatedly listen for leaks over a predefined decision horizon. This way we avoid constant monitoring of the system. While we found the detection of leaks in close proximity to be a trivial task for almost all models, neural network based approaches achieve better results at the detection of distant leaks.

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Paper citation in several formats:
Müller, R. ; Illium, S. ; Ritz, F. ; Schröder, T. ; Platschek, C. ; Ochs, J. and Linnhoff-Popien, C. (2021). Acoustic Leak Detection in Water Networks. In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-484-8; ISSN 2184-433X, SciTePress, pages 306-313. DOI: 10.5220/0010295403060313

@conference{icaart21,
author={Robert Müller and Steffen Illium and Fabian Ritz and Tobias Schröder and Christian Platschek and Jörg Ochs and Claudia Linnhoff{-}Popien},
title={Acoustic Leak Detection in Water Networks},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2021},
pages={306-313},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010295403060313},
isbn={978-989-758-484-8},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Acoustic Leak Detection in Water Networks
SN - 978-989-758-484-8
IS - 2184-433X
AU - Müller, R.
AU - Illium, S.
AU - Ritz, F.
AU - Schröder, T.
AU - Platschek, C.
AU - Ochs, J.
AU - Linnhoff-Popien, C.
PY - 2021
SP - 306
EP - 313
DO - 10.5220/0010295403060313
PB - SciTePress

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