Pipeline Leak Detection Using the Matched-Field Processing Method

Wang, Xun; Ghidaoui, Mohamed Salah

doi:10.1061/(asce)hy.1943-7900.0001476

Cited by 87 publications

(68 citation statements)

References 36 publications

(40 reference statements)

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“…Consequently, the spacing of potential leaks is advised to be equal to half of minimum wavelength. This result is in agreement with the Nyquist-Shannon theory (Shannon 1949) and recent studies of transient-based leak detection by Wang and Ghidaoui (2018b) that two leaks with a distance lower than half of the minimum wavelength cannot be identified.…”

Section: Spatial Resolution Of Leak Estimatessupporting

confidence: 91%

“…In addition, the CRLB shows that the larger the value of J (number of measured frequencies), the smaller the variance of the leak estimate. This dependence on frequency provides a theoretical support for the intuitive result that sharper transients (wider frequency bandwidth) result in more reliable (accurate) defect detection and agrees with the results found by Lee et al (2013Lee et al ( , 2015, Zhao et al (2018), Louati et al (2017), and Wang and Ghidaoui (2018b).…”

Section: Crlb and Its Role In Transient-based Defect Detectionsupporting

confidence: 86%

“…These errors mean that TBDDM results need to be interpreted using a statistical framework (Duan 2016;Sattar and El-Beltagy 2017). This approach for TBDDM is in its infancy, but is beginning to bear fruit (e.g., Vitkovsky et al 2007;Lee et al 2015;Wang and Ghidaoui 2018b;Zhao et al 2018).…”

Section: Introductionmentioning

confidence: 99%

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Cramer-Rao Lower Bound for Performance Analysis of Leak Detection

et al. 2019

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Due to random noise in real measurements, leak detection (estimation of leak size and location) is subject to a degree of uncertainty. This paper provides a framework to investigate the lower bound of the variance of a leak's variable estimation and delineates the parameters upon which this lower bound depend. This is accomplished by applying the Cramer-Rao lower bound (CRLB) principle to the leak detection problem. For a given data set, CRLB gives the minimum mean square error of any unbiased estimator. The CRLB is evaluated using the Fisher information, which is evaluated from direct differentiation of the water-hammer characteristics equations. The results show that the CRLB of the leak-size estimate increases with time of closure and noise level but reduces with the duration of the measured signal. It is also shown that the CRLB is instrumental in the systematic design of efficient transient tests for leak detection. The error of leak-size estimates rises remarkably with setting distances between consecutive potential leaks of less than half the minimum wavelength of the probing signal. More conclusions are drawn on appropriate mesh-size for inverse transient analysis (ITA), maximum possible accuracy in successful localization, and its probability subject to the physical situation's parameters.

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Section: Spatial Resolution Of Leak Estimatessupporting

confidence: 91%

Section: Crlb and Its Role In Transient-based Defect Detectionsupporting

confidence: 86%

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Cramer-Rao Lower Bound for Performance Analysis of Leak Detection

et al. 2019

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“…Wang and Ghidaoui (2018a) showed that the modal-interdependence terms for multiple leaks involve products of the usually small leak sizes and used this fact to arrive at a linear relation between measured pressure head and unknown parameters of the leaks. Based on this expression, Wang and Ghidaoui (2018b) proposed a matched-field processing (MFP) approach able to identify a leak based on a 1D search of leak location along the pipe independent of the leak size, which was proven to be robust with respect to a high level of noise. However, it was found that the presence of local maxima in the objective function of MFP may interfere with the judgment of leak location.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, three beamforming techniques (Bartlett's, Capon's, and Lagunas' BFs) and a subspace-based method [multiple signal classification (MUSIC)] are used for pipeline leak localization. Bartlett's BF is equivalent to the MFP method of Wang and Ghidaoui (2018b), which has the drawback that its objective function has high local maxima. The present paper generalizes that method to derive other versions of spectral-based methods, which are able to obtain a unique leak localization.…”

Section: Introductionmentioning

confidence: 99%

Spectral-Based Methods for Pipeline Leakage Localization

et al. 2019

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In this paper, the pipeline leak localization problem using transient data is investigated. Signal processing techniques that proved successful in wireless communications and acoustics are adapted and tested for leak identification. More specifically, Bartlett's beamforming (BF) (also known as conventional BF, matched field, or phased array), Capon's BF (also known as the minimum variance distortionless response filter), Lagunas' BF, and multiple signal classification (MUSIC) methods are used. The localization is realized by a one-dimensional search for the leak location along the pipe, where one-dimensional search means that the wave model used includes one leak only. The one-dimensional search is advantageous in that it involves low computational cost. The performance of the different techniques in the cases of a single leak and multiple leaks is discussed. In the single-leak case, the proposed spectral methods accurately localize the leak even for a high level of noise. For the multiple-leak case, the proposed spectral methods are able to localize all leaks provided that the leak-to-leak distance is of the same order or larger than half the shortest probing wavelength. However, the localization deteriorates when the leaks are too close together because a model with a single leak is being used to identify multiple leaks. Although not accurate, the application of the one-dimensional search to multiple leaks is still valuable because it provides a fast initial estimate of the leak locations, which serves as prior information for more precise but computationally expensive multidimensional search techniques.

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State‐of‐the‐art review of leak diagnostic experiments: Toward a smart water network

Bakhtawar

Zayed

2023

WIREs Water

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Effective water pipeline leak detection and localization can help water practitioners save water losses and reduce pipe rehabilitation budgets. Different sensing technologies can provide essential data aiding model development for predicting future leaks in the water distribution networks. Solutions for applying different sensing technologies to real water distribution networks are being developed for real‐time data collection, precise leak localization, reducing false alarms, and continuous pipeline monitoring. Experiments of different scales and specifications have been conducted to test the application and effectiveness of sensing technologies for leak diagnosis in water pipelines. Quality data collection is especially crucial for the successful implementation of these experiments. However, practitioners need help designing effective leak detection and localization experiments, wasting time, and resources. There needs to be a greater understanding of the design parameters for more accurate testing, such as sensor selection, sensor placement, ambient noise sources, and system operations. The current study, therefore, delineates design parameters for design leak diagnosis experiments for lab, testbed, and real networks. For application in real water networks, expert opinion is used to help identify the benefits and limitations and the implementation issues of available sensing technologies. An example experiment design using multi‐sensing technologies for smart leak diagnostics in Hong Kong is also presented. The study can guide water practitioners and researchers to design a multi‐sensing leak diagnostic experiments enabling a smart and sustainable utility management.This article is categorized under: Engineering Water > Methods Engineering Water > Sustainable Engineering of Water Science of Water > Water Extremes

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Pipeline Leak Detection Using the Matched-Field Processing Method

Cited by 87 publications

References 36 publications

Cramer-Rao Lower Bound for Performance Analysis of Leak Detection

Cramer-Rao Lower Bound for Performance Analysis of Leak Detection

Spectral-Based Methods for Pipeline Leakage Localization

State‐of‐the‐art review of leak diagnostic experiments: Toward a smart water network

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