DeepAI AI Chat
Log In Sign Up

Acoustic Leak Detection in Water Networks

by   Robert Müller, et al.

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.


page 3

page 5


SAM-kNN Regressor for Online Learning in Water Distribution Networks

Water distribution networks are a key component of modern infrastructure...

Acoustic Anomaly Detection for Machine Sounds based on Image Transfer Learning

In industrial applications, the early detection of malfunctioning factor...

Deep Learning for Prawn Farming: Forecasting and Anomaly Detection

We present a decision support system for managing water quality in prawn...

Underwater Acoustic Networks for Security Risk Assessment in Public Drinking Water Reservoirs

We have built a novel system for the surveillance of drinking water rese...

Anomaly Detection in Energy Usage Patterns

Energy usage monitoring on higher education campuses is an important ste...