Passive detection in water pipelines using ambient noise II: Field experiments. (1st December 2022)

• Record Type: Journal Article
• Authors: Li, Zhao; Lee, Pedro; Fink, Mathias; Murch, Ross; Davidson, Mark
• Is Part Of: Mechanical systems and signal processing. Volume 181(2022)
• Publication Date: 2022-12-01
• Subjects: Inverse scattering -- Passive detection -- Ambient noise -- Water pipelines -- Field experiment; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2022.109524
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: A passive detection method has been proposed in a prior paper to extract key parameters and detect faults using the ambient noise present in water pipeline networks. This paper presents field experiments and data processing results to provide systematic experimental validation of this method. Field experiments were carried out in operational water pipeline networks at the University of Canterbury campus and the Waimakariri District, New Zealand, during which ambient noise was measured by pairs of pressure sensors installed at selected hydrants on pipelines of different materials, network topologies and simulated faults. Auto-correlation and cross-correlation analysis of noise at a single sensor and sensor pairs were carried out to estimate the wave speed and to locate faults in the networks. Data processing results indicate that water usage generating pressure transients are the dominant sources of ambient noise in operational water pipeline networks. This type of ambient noise can also be utilized by the passive detection method to achieve similar wave speed estimation accuracy and fault detection performance as the conventional active pressure wave detection methods. Highlights: Field experiments verified that pipe condition can be assessed using ambient noise. Field experiments verified that pipeline faults can be detected using ambient noise. Pressure transients caused by water usage are the dominant coherent noise sources. Wave speed passively estimated by noise is as accurate as traditional active methods. Blockage and leak faults can be detected by noise auto-correlation with 3 m accuracy.