Forecasting Leak Localization in Municipal Water Pipelines with Acoustic Sensing Arrays

Abstract

The rapid escalation of global urbanization has placed unprecedented stress on municipal water distribution networks, necessitating highly accurate and efficient leak detection mechanisms to mitigate non-revenue water loss. This paper presents a comprehensive investigation into predicting leak localization within municipal water pipelines through the deployment of advanced acoustic sensing arrays. By leveraging a comparative analytical framework, this study evaluates the efficacy of multiple acoustic signal processing methodologies and spatial localization algorithms under complex environmental conditions. Utilizing high-fidelity acoustic data captured from a scaled municipal pipeline testbed, various sensor modalities including hydrophones, accelerometers, and surface-mounted vibration sensors are systematically compared. The research explores the intricate dynamics of acoustic wave propagation, attenuation characteristics, and background noise interference inherent in underground infrastructure. Through rigorous temporal and spectral analysis, the comparative performance of cross-correlation techniques, transient wave analysis, and data-driven anomaly detection models is quantified. The findings reveal that distributed acoustic sensing arrays, when paired with adaptive noise cancellation and multivariate feature extraction, significantly enhance localization precision while reducing false positive rates. This study provides critical insights for civil engineers and urban infrastructure managers, offering a robust methodological foundation for deploying intelligent acoustic networks that can proactively secure urban water resources and optimize predictive maintenance schedules.