Multi‐Sensor Fusion for Transient‐Based Pipeline Leak Localization in the Dempster‐Shafer Evidence Framework

Abstract

Leakage in urban water supply systems results in huge financial loss. The World Bank estimates the worldwide monetary value of loss water at about 39 billion USD per year (Liemberger & Wyatt, 2019). This is direct water cost; leakage also gives rise to indirect socioeconomic costs as pipe failures may disrupt businesses, interrupt production processes, cause floods, and damage properties (Huang et al., 2020). In addition, leaks are potential entry points for contaminants and thus lead to risks to public health (Colombo et al., 2009;. Therefore, a fast, accurate and low-cost leak localization method is of desperate need.Fluid transient-based defect detection methodology is a promising general approach for estimating leaks and other defects and has been intensively investigated in the last three decades. This approach actively introduces hydraulic waves, measures pressure response at specified location(s), and analyzes the measured signals to identify and localize defects in a pipe system. This approach can be divided into two classes: (i) the model-data matching methods and (ii) the signal feature methods. The model-data matching methods estimate the concerned parameters (such as leak location and size) by matching pressure measurement with either (i-a) time-domain model (

Leak Localization in Looped Pipe Networks Based on a Factorized Transient Wave Model: Theoretical Framework

“…The urban water distribution systems tend to be complicated and riddled with various natural (e.g., turbulence) and artificial (e.g., traffic) noise and uncertainties with large amplitude (Alawadhi et al., 2018; Alawadhi & Tartakovsky, 2020; Ferrante et al., 2014; Lin et al., 2021; X. Wang, 2021a; X. Wang, Waqar, et al., 2020; Waqar et al., 2021). To address the noise problem, the matched‐field processing (MFP), which is a parameter estimation technique that is based on the principle of maximum signal‐to‐noise ratio and thus robust in noisy and uncertain environments, was first adopted by X. Wang and Ghidaoui (2018b) for leak localization in a single pipe.…”

“…The urban water distribution systems tend to be complicated and riddled with various natural (e.g., turbulence) and artificial (e.g., traffic) noise and uncertainties with large amplitude (Alawadhi et al, 2018;Alawadhi & Tartakovsky, 2020;Ferrante et al, 2014;Lin et al, 2021;X. Wang, 2021a;X.…”

Leak Localization in Looped Pipe Networks Based on a Factorized Transient Wave Model: 2. Regularization of Ill‐Conditioned Problems

“…Although the transient wave‐based methods in the literature (Duan, 2017; Kim, 2020; Liggett & Chen, 1994) have shown their potential for leak localization in looped pipe networks (hereinafter called looped networks), these existing methods are mainly suited for pipe systems in relatively quiet environments where the amplitude of desired wave signals is an order of magnitude larger than that of background noise. Urban water distribution systems are usually exposed to a myriad of natural and artificial noise sources, such as turbulent fluctuations, ground traffic flows, and air bubble collapse (Dubey et al., 2019; Lin et al., 2021; Wang, 2021a). The generated background noise would easily result in the inaccuracy or even invalidity of the existing leak localization methods.…”

Efficient Pipe Burst Detection in Tree‐Shape Water Distribution Networks Using Forward‐Backward Transient Analysis

“…The leak or burst detection is a potential use of transient waves (Lin et al., 2021; X. Wang, 2021). During wave propagation, the interaction between the wave and defects will modify the signal, and based on the modification, a defect can be localized (Che et al., 2021; Duan et al., 2020; Louati et al., 2020).…”