Acoustic Detection of Leaks in Water Pipelines Using Measurements inside Pipe

Khulief, Y. A.; Khalifa, Atia E.; Ben‐Mansour, Rached; Habib, Mohamed A.

doi:10.1061/(asce)ps.1949-1204.0000089

Cited by 140 publications

(61 citation statements)

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“…For this purpose, the sensitivity matrix (2) has been computed using ( considering only one sample in the leak location diagnosis (N = 1), are summarized in Table 3. The values presented in the table correspond to the overall accuracy Ac defined in (6). As it can be seen, both methods provide good performances in the leak uncertainty case thanks to the linear directional variation of most of the residuals for this kind of uncertainty.…”

Section: Hanoi Case Studymentioning

confidence: 97%

“…Recently developed acoustic instruments [6] allow to locate also invisible leaks, but unfortunately, their application over a large-scale water network is very expensive and time-consuming. A viable solution is to divide the network into District Metered Areas (DMA), where the flow and the pressure at the input are measured [7,1], and to maintain a permanent leakage control-system: leakages in fact increase the flow and decrease the pressure measurements at the DMA entrance.…”

Section: Introductionmentioning

confidence: 99%

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Leak localization in water distribution networks using a mixed model-based/data-driven approach

Soldevila¹,

Blesa

Tornil-Sin

et al. 2016

Control Engineering Practice

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This paper proposes a new method for leak localization in water distribution networks (WDNs). In a first stage, residuals are obtained by comparing pressure measurements with the estimations provided by a WDN model. In a second stage, a classifier is applied to the residuals with the aim of determining the leak location. The classifier is trained with data generated by simulation of the WDN under different leak scenarios and uncertainty conditions. The proposed method is tested both using synthetic and experimental data with real WDNs of different sizes. The comparison with the current existing approaches shows a performance improvement.

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Section: Hanoi Case Studymentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Leak localization in water distribution networks using a mixed model-based/data-driven approach

Soldevila¹,

Blesa

Tornil-Sin

et al. 2016

Control Engineering Practice

View full text Add to dashboard Cite

show abstract

“…More precisely, each simulated fault scenario is performed by injecting a leak of a magnitude of f j in the j th DMA network node in order to compute the sensitivity vector (2). For the sake of simplicity and without loss of generality, m possible leaks (one for each node) have been assumed.…”

Section: Leak Location Methodologymentioning

confidence: 99%

Optimal sensor placement for leak location in water distribution networks using genetic algorithms

Casillas

Puig

Garza-Castañón

et al. 2013

2013 Conference on Control and Fault-Tolerant Systems (SysTol)

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This paper proposes a new sensor placement approach for leak location in water distribution networks (WDNs). The sensor placement problem is formulated as an integer optimization problem. The optimization criterion consists in minimizing the number of non-isolable leaks according to the isolability criteria introduced. Because of the large size and non-linear integer nature of the resulting optimization problem, genetic algorithms (GAs) are used as the solution approach. The obtained results are compared with a semi-exhaustive search method with higher computational effort, proving that GA allows one to find near-optimal solutions with less computational load. Moreover, three ways of increasing the robustness of the GA-based sensor placement method have been proposed using a time horizon analysis, a distance-based scoring and considering different leaks sizes. A great advantage of the proposed methodology is that it does not depend on the isolation method chosen by the user, as long as it is based on leak sensitivity analysis. Experiments in two networks allow us to evaluate the performance of the proposed approach.

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“…However, this approach still presents issues related to the size of the virtual partition that would require further improvement. Recently, acoustic instruments that allow the location of invisible leaks were developed by [9], but unfortunately, their application to a large-scale water network is very expensive and time-consuming. Another leak detection methodology based on the generation of a new class of structured residuals has been proposed in [10] and satisfactorily applied to a water distribution network.…”

Section: Introductionmentioning

confidence: 99%

Leak Signature Space: An Original Representation for Robust Leak Location in Water Distribution Networks

Casillas

Garza-Castañón

Puig

et al. 2015

Water

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In this paper, an original model-based scheme for leak location using pressure sensors in water distribution networks is introduced. The proposed approach is based on a new representation called the Leak Signature Space (LSS) that associates a specific signature to each leak location being minimally affected by leak magnitude. The LSS considers a linear model approximation of the relation between pressure residuals and leaks that is projected onto a selected hyperplane. This new approach allows to infer the location of a given leak by comparing the position of its signature with other leak signatures. Moreover, two ways of improving the method's robustness are proposed. First, by associating a domain of influence to each signature and second, through a time horizon analysis. The efficiency of the method is highlighted by means of a real network using several scenarios involving different number of sensors and considering the presence of noise in the measurements.

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Acoustic Detection of Leaks in Water Pipelines Using Measurements inside Pipe

Cited by 140 publications

References 1 publication

Leak localization in water distribution networks using a mixed model-based/data-driven approach

Leak localization in water distribution networks using a mixed model-based/data-driven approach

Optimal sensor placement for leak location in water distribution networks using genetic algorithms

Leak Signature Space: An Original Representation for Robust Leak Location in Water Distribution Networks

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