Model falsification diagnosis and sensor placement for leak detection in pressurized pipe networks

Goulet, James‐A.; Coutu, Sylvain; Smith, Ian F. C.

doi:10.1016/j.aei.2013.01.001

Cited by 107 publications

(63 citation statements)

References 27 publications

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“…In general, hydraulic models for water networks are widely known and used (Brdys & Ulanicki, 1994) and in several approaches, hydraulic modelling has also been used for leakage localization techniques: (Ligget & Chen, 1995;Mandel, 1998;Kapelan et al, 2003;Almandoz et al, 2005;Brown, 2007;Wu et al 2010;Goulet et al 2013). In these cases, the dependence of leaks on pressure (Greyvenstein, 2007;Lambert, 1997) is the keystone in the detection, localisation and control.…”

Section: Water Distribution System: Mathematical Modelingmentioning

confidence: 99%

A decision support system for on-line leakage localization

Meseguer

Mirats-Tur

Cembraño

et al. 2014

Environmental Modelling & Software

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Abstract:This paper describes a model-driven decision-support system (software tool) implementing a model-based methodology for on-line leakage detection and localization which is useful for a large class of water distribution networks. Since these methods present a certain degree of complexity which limits their use to experts, the proposed software tool focuses on the integration of a method emphasizing its use by water network managers as a decision support system. The proposed software tool integrates a model-based leakage localization methodology based on the use of on-line telemetry information, as well as a water network calibrated hydraulic model. The application of the resulting decision support software tool in a district metered area (DMA) of the Barcelona distribution network is provided and discussed. The obtained results show that the leakage detection and localization may be performed efficiently reducing the required time.

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Section: Water Distribution System: Mathematical Modelingmentioning

confidence: 99%

A decision support system for on-line leakage localization

Meseguer

Mirats-Tur

Cembraño

et al. 2014

Environmental Modelling & Software

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“…This framework is based on error-domain model falsification which has been found to be useful in applications of bridge diagnosis and leak detection in water networks [16,18]. In such systems, parameter values are identified using measurements carried out only at specific times.…”

Section: ) Methodologymentioning

confidence: 99%

“…If incorrect probability distributions are defined, it may lead to over-conditioning of parameter values [14]. Furthermore, modeling errors are often systematic and this introduces additional error correlations between measurement locations [16,17]. Implementation of Bayesian inference requires a complete knowledge of all correlations in order to avoid biased predictions.…”

Section: ) Introductionmentioning

confidence: 99%

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A model-based data-interpretation framework for improving wind predictions around buildings

Vernay

Raphael

Smith

2015

Journal of Wind Engineering and Industrial Aerodynamics

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Abstract:Although Computational Fluid Dynamics (CFD) simulations are often used to assess wind conditions around buildings, the accuracy of such simulations is often unknown. This paper proposes a datainterpretation framework that uses multiple simulations in combination with measurement data to improve the accuracy of wind predictions. Multiple simulations are generated through varying sets of parameter values. Sets of parameter values are falsified and thus not used for predictions if differences between measurement data and simulation predictions, for any measurement location, are larger than an estimate of uncertainty bounds. The bounds are defined by combining measurement and modelling uncertainties at sensor locations. The framework accounts for time-dependent and spatially-distributed modelling uncertainties that are present in CFD simulations of wind. The framework is applied to the case study of the CREATE Tower located at the National University of Singapore. Values for timedependent inlet conditions, as well as values for the roughness of surrounding buildings, are identified with measurements carried out around the CREATE Tower. Results show that, on average, ranges of

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“…All of these techniques are based on transient analysis, which is mainly used on single, grounded pipelines due to the high effect of the system uncertainty on results. Non-transient modelbased leakage localization techniques have been also developed during the last years [ (Wu and Sage 2006); (Pérez et al 2011); (Wu et al 2010); (Farley et al 2011); (Goulet et al 2013); ]. These techniques analyze the difference between measurements and estimated values from leaky scenarios to signal the probability of a zone to contain leakage.…”

Section: Introductionmentioning

confidence: 99%

Leak Detection and Localization through Demand Components Calibration

Sanz

Pérez

Kapelan

et al. 2016

J. Water Resour. Plann. Manage.

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The success in the application of any model-based methodology (e.g. design, control, supervision) highly depends on the availability of a well calibrated model. The calibration in water distribution networks needs to be performed online due to the continuous evolution of demands. During the calibration process, background leakages or bursts can be unintentionally incorporated to the demand model and treated as a system evolution (change in demands). This work proposes a leak detection and localization approach to be coupled with a calibration methodology that identifies geographically distributed parameters. The approach proposed consists in comparing the calibrated parameters with their historical values to assess if changes in these parameters are caused by a system evolution or by the effect of leakage. The geographical distribution allows to associate an unexpected behavior of the calibrated parameters (e.g. abrupt changes, trends, etc.) to a specific zone in the network. The performance of the methodology proposed is tested on a real water distribution network using synthetic data. Tested scenarios include leaks occurring at different locations and ranging from 2.5% to 13% of the total consumption. Leakage is represented as pressure-dependent demand simulated as emitter flows at the network nodes. Results show that even considering a low number of sensors, leaks with an effect on parameters higher than the parameters' uncertainty can be correctly detected and located within 200 meters.

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Model falsification diagnosis and sensor placement for leak detection in pressurized pipe networks

Cited by 107 publications

References 27 publications

A decision support system for on-line leakage localization

A decision support system for on-line leakage localization

A model-based data-interpretation framework for improving wind predictions around buildings

Leak Detection and Localization through Demand Components Calibration

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