Field testing of an optimal sensor placement methodology for event detection in an urban water distribution network

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

doi:10.1080/1573062x.2010.526230

Cited by 70 publications

(38 citation statements)

References 9 publications

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“…An alternative approach based on an inverse approach that formulates the leak detection and localization problem as a parameter estimation approach was presented by Pudar & Ligget (1992) and further inverse approaches were investigated (Ligget & Chen, 1995) (Kapelan et al, 2003) (Wu & Sage, 2006). Additionally, other contributions integrating data-driven and model-driven approaches (Farley et al, 2010;Bicik et al, 2013) or based just on a data-driven approach (Romano et al, 2013) were also presented. Pérez et al (2011) presents a direct modelling methodology developed to help network operators deal with the detection and localization of leaks in district metered areas (DMAs 5 ) of water distribution networks.…”

Section: Introductionmentioning

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: Introductionmentioning

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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“…Data was collected from the pressure instruments located inside each DMA, including the current DG2 location, and at the most sensitive (or optimal) location previously identified by a Jacobean matrix approach. Analysis of pressure measurements recorded before, during, and after the burst events were used to evaluate the sensitivity of each instrument location to the pressure changes caused by the simulated burst events (Farley et al, 2010a). Figure 1 shows model predicted, and actual sensitivities for 5 simulated bursts at eight instrumentation points in a single DMA highlighting the correlation between predicted (model) and actual (real) sensitivities.…”

Section: Instrument Location and Dma Subdivisionmentioning

confidence: 99%

“…If the most sensitive locations were determined, more fluctuations and events would be detected and awareness of system performance increased; for example, more burst pipes can be identified, and more accurate estimates of the number of customers suffering low pressure, over what duration, can be determined. A method to identify optimal locations for pressure instruments used for detection and location of leak/burst events was developed by Farley et al (2008Farley et al ( , 2010a. The approach utilised a methodology that searches a Jacobian sensitivity matrix produced by sequentially modelling leak/burst events at all nodes in a 1-D hydraulic model, and evaluating the change in pressure response at all possible instrument locations.…”

Section: Instrument Location and Dma Subdivisionmentioning

confidence: 99%

“…The current placement of instrumentation in water distribution networks in the UK is to meet the requirement to monitor and report leakage and low pressure; but measurement locations are not always the most sensitive for this purpose. Automated techniques have therefore been developed to identify these optimal locations (Perez et al, 2009(Perez et al, , 2011Farley et al, 2008Farley et al, , 2010aRosich et al, 2012;Preis et al, 2011;Goulet et al, 2013) and continue to be improved.…”

Section: Opportunitymentioning

confidence: 99%

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Online data processing for proactive UK water distribution network operation

Machell

Mounce

Farley

et al. 2014

Drink. Water Eng. Sci.

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Abstract. Operational benefits and efficiencies generated using prevalent water industry methods and techniques are becoming more difficult to achieve; as demonstrated by English and Welsh water companies' static position with regards the economic level of leakage. Water companies are often unaware of network incidents such as burst pipes or low pressure events until they are reported by customers; and therefore use reactive strategies to manage the effects of these events. It is apparent that new approaches need to be identified and applied to promote proactive network management if potential operational productivity and standards of service improvements are to be realised. This paper describes how measured flow and pressure data from instrumentation deployed in a UK water distribution network was automatically gathered, checked, analysed and presented using recently developed techniques to generate apposite information about network performance. The work demonstrated that these technologies can provide early warning, and hence additional time to that previously available, thereby creating opportunity to proactively manage a network; for example to minimise the negative impact on standards of customer service caused by unplanned events such as burst pipes.Each method, applied individually, demonstrated improvement on current industry processes. Combined application resulted in further improvements; including quicker and more localised burst main location. Future possibilities are explored, from which a vision of seamless integration between such technologies emerges to enable proactive management of distribution network events.

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“…For instance, Aksela et al [27] uses the knowledge of reported leak experience with the data collected from flow meter readings to model and train the system. Farley et al [28] presented a methodology for the detection of pipe burst, achieved by identifying the optimal locations of pressure sensors. Similarly, a sensor placement and leakage detection methodology to identify leakages in a WDS based on the deviation of sensor pressure from an estimated pressure was presented by Perez et al [29].…”

Section: Background and Related Workmentioning

confidence: 99%

Leakage Detection and Estimation Algorithm for Loss Reduction in Water Piping Networks

Adedeji

Hamam

Abe

et al. 2017

Water

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Water loss through leaking pipes constitutes a major challenge to the operational service of water utilities. In recent years, increasing concern about the financial loss and environmental pollution caused by leaking pipes has been driving the development of efficient algorithms for detecting leakage in water piping networks. Water distribution networks (WDNs) are disperse in nature with numerous number of nodes and branches. Consequently, identifying the segment(s) of the network and the exact leaking pipelines connected to this segment(s) where higher background leakage outflow occurs is a challenging task. Background leakage concerns the outflow from small cracks or deteriorated joints. In addition, because they are diffuse flow, they are not characterised by quick pressure drop and are not detectable by measuring instruments. Consequently, they go unreported for a long period of time posing a threat to water loss volume. Most of the existing research focuses on the detection and localisation of burst type leakages which are characterised by a sudden pressure drop. In this work, an algorithm for detecting and estimating background leakage in water distribution networks is presented. The algorithm integrates a leakage model into a classical WDN hydraulic model for solving the network leakage flows. The applicability of the developed algorithm is demonstrated on two different water networks. The results of the tested networks are discussed and the solutions obtained show the benefits of the proposed algorithm. A noteworthy evidence is that the algorithm permits the detection of critical segments or pipes of the network experiencing higher leakage outflow and indicates the probable pipes of the network where pressure control can be performed. However, the possible position of pressure control elements along such critical pipes will be addressed in future work.

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Field testing of an optimal sensor placement methodology for event detection in an urban water distribution network

Cited by 70 publications

References 9 publications

A decision support system for on-line leakage localization

A decision support system for on-line leakage localization

Online data processing for proactive UK water distribution network operation

Leakage Detection and Estimation Algorithm for Loss Reduction in Water Piping Networks

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