A Survey of Water Pipeline Leak Detection Using Acoustic Sensing

Water transmission and distribution infrastructures are essential assets within urban communities and crucial for maintaining a reliable and efficient water supply. The aging of water mains can lead to water loss, environmental contamination, and service disruptions. Acoustic-based leak detection methods have become a key approach because they can detect small leaks and are cost-effective. This paper reviews both traditional and state-of-the-art acoustic detection techniques, focusing on the integration of machine learning approaches. Machine learning-based approaches have shown promising accuracy and efficiency in recent years. The survey covers several key areas, including the characterization of common leak types, the deployment of acoustic sensors, the general framework for acoustic leak detection processes (highlighting the role of conventional machine learning and deep learning in processing acoustic signals for leak detection), and the research challenges in this field. This article presents an overview of recent advances in acoustic leak detection technologies, providing a guide to select suitable approaches based on data availability and research requirements. It also identifies prospective research areas for water pipeline inspection studies.