Field Validation of "Optimal" Instrumentation Methodology for Burst/Leak Detection and Location

Farley, B.; Mounce, S. R.; Boxall, Joby

doi:10.1061/41203(425)99

Cited by 9 publications

(8 citation statements)

References 2 publications

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“…The method presented here builds on and develops work by Farley et al (2008Farley et al ( , 2010aFarley et al ( , and 2010b, to provide a technique which is able to both detect and localise burst events within WDS.…”

Section: Methodsmentioning

confidence: 99%

“…{Figure 1 approximately here} To utilise this approach it is necessary to determine likely instrument behaviour at different locations with sufficient accuracy to identify differential sensitivity in real, complex networks. The work by Farley et al (2008Farley et al ( , 2010aFarley et al ( , and 2010b) utilised a methodology that produces such a sensitivity matrix.…”

Section: Methodsmentioning

confidence: 99%

“…Research has been conducted in the application of multiple hydraulic simulation and GA search approaches to burst event detection. A methodology for optimal placement of pressure instruments for improved detection was first proposed in Farley et al (2008), and fully presented with field validation in a real water distribution system in Farley et al (2010a). Perez et al (2009) presented a similar method for identifying burst events, however the method was reliant on heavily instrumenting networks with more than fifteen sensors and has not been tested on in real WDS with simulated or real events.…”

Section: Introductionmentioning

confidence: 99%

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Development and Field Validation of a Burst Localization Methodology

Farley

Mounce

Boxall

2013

J. Water Resour. Plann. Manage.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Development and Field Validation of a Burst Localization Methodology

Farley

Mounce

Boxall

2013

J. Water Resour. Plann. Manage.

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“…The first discussion and analysis of OSP for leak localization emerged in 2008 with the work of Farley et al (2008Farley et al ( , 2010Farley et al ( , 2013, followed in 2009 by Pérez et al (2009). Both OSP approaches are based on the leak sensitivity matrix.…”

Section: Introductionmentioning

confidence: 99%

Efficient Sensor Placement for Leak Localization Considering Uncertainties

Steffelbauer

Fuchs-Hanusch

2016

Water Resour Manage

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Losses in water distribution systems can be between several percent in well maintained systems up to more than 50 percent in developing countries. Most of the losses originate from leaks. Therefore, a fast detection and localization of leaks is crucial for effectively reducing this losses in water distribution networks. Model-based leak localization has become increasingly popular in recent years. Certainly, the performance of these methods is linked to 1) the measurement locations in the system and 2) uncertainties at these locations. This paper provides a methodology that incorporates uncertainties of different types and sources in the optimal sensor placement problem for leak localization shown by the example of the effect of demand uncertainties on potential pressure measurement points. The problem is solved for different numbers of sensors and different strengths of uncertainties are taken into account. Additionally, to describe the relation between the number of sensors and the leak localization quality, a cost-benefit function is derived based on the different sensor placement results and GoF statistics. It was found that the function follows a power law. Results show that incorporating uncertainties leads to other optimal positions than without uncertainties, but the power law behavior still stays true. Additionally, more sensors are needed than without uncertainties.

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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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Field Validation of "Optimal" Instrumentation Methodology for Burst/Leak Detection and Location

Cited by 9 publications

References 2 publications

Development and Field Validation of a Burst Localization Methodology

Development and Field Validation of a Burst Localization Methodology

Efficient Sensor Placement for Leak Localization Considering Uncertainties

Leak Detection and Localization through Demand Components Calibration

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