Low-cost failure sensor design and development for water pipeline distribution systems

Khan, Asar; Widdop, Peter D.; Day, Andrew J.; Wood, Alastair S.; Mounce, S. R.; Machell, John

doi:10.2166/wst.2002.0588

Cited by 3 publications

(3 citation statements)

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“…A neural network knowledge-based system was developed for automatic and continuous monitoring of the measured data for normal and abnormal behavior. As a part of the same work, Khan et al (2002) developed a low-cost failure sensor design. The design of sensors was based on correlation between abnormal flows and the opacity of the water.…”

Section: Static Mass Balancementioning

confidence: 99%

Modeling of Hydraulic Load of Electric Drive in Electrical Complex of Pumping Station

Lysiak¹,

Oliinyk²,

Shelekh³

2018

Energy eng. control syst.

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Sudden pipe bursts occur in high-pressure water transmission pipelines and water distribution networks. The consequences of these bursts can be very expensive due to the outage time while the burst pipe is repaired, the cost of repair, and damage to surrounding property and infrastructure. As a result, it is advantageous to minimise the detection and location time after the burst occurs.Currently, there is no effective solution for the burst detection and location problem in water distribution systems. The applications in oil and gas pipelines and pipe networks show the advantages of continuous monitoring. A number of techniques are used to determine the location and size of a burst. One of the most promising approaches is fluid transient modelling and analysis. Pressure transient analysis has also been successfully applied for detection and location of existing leaks.A sudden pipe burst creates a negative pressure wave that travels in both directions away from the burst point. The analysis of this wave is the main principle for the techniques presented in this thesis. Experiences from previous research suggest that, to achieve the best performance, single pipelines and pipe networks have to be treated separately. Thus, two different approaches for burst detection and location are presented.When a burst occurs in a pipeline, the burst-induced pressure wave travels in both directions along the pipeline and is reflected at the boundaries. Using a pressure trace measured at one location along the pipeline, the timing of the initial and reflected burst-induced waves determines the location of the burst. The presented continuous monitoring technique uses the modified two-sided cumulative sum (CUSUM) algorithm to detect abrupt changes in the pressure iii data caused by the pipe break. The results from both laboratory and field pipelines are used to verify the proposed method. Different burst and measurement locations are tested. The results are promising for burst detection and location in real systems.In the network case, continuous pressure measurements at two locations are analysed. The burst detection and location algorithm is based on the difference between the arrival times of the burst-induced pressure wave at each measurement point and on the measured wave magnitude. The arrival times are determined automatically in real time. A method for determining optimal measurement locations is also presented. Results from numerical simulations show that the proposed technique has potential as a tool for effective detection and location of bursts in real pipe networks.

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Section: Static Mass Balancementioning

confidence: 99%

Modeling of Hydraulic Load of Electric Drive in Electrical Complex of Pumping Station

Lysiak¹,

Oliinyk²,

Shelekh³

2018

Energy eng. control syst.

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“…where v is the propagation speed of the leak acoustic signal along the monitored pipeline, l is the length of pipeline between sensing points, D is the estimate of D by the time delay estimation techniques [1,6]. In equation (2), in order to locate the leak, we can see that the accurate pipeline length between the sensing points is a necessity. However, in practice, this necessity is not always satisfied.…”

Section: Detection Modelmentioning

confidence: 99%

“…Water pipeline leaks are a growing concern around the world since water leaks will create risks to public safety and health as well as result in a waste of resources [1]. Thus, to reduce public health risk, to protect the environment and particularly to preserve public drinking water, the ideal way is to implement serious leakage control methods to predict and detect leaks in water distribution systems [2][3][4][5]. They can be used to prioritize areas for leak location procedures.…”

Section: Introductionmentioning

confidence: 99%

The genetic-algorithm-enhanced blind system identification for water distribution pipeline leak detection

Yang¹,

Wen²,

Li³

2007

Meas. Sci. Technol.

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The conventional leak location is based on the correlation of leak acoustic signals acquired spatially separately. By correlation, the time lag is estimated for localizing the leakage. In these methods, the detection distance is a prerequisite that has to be known beforehand. However, in practice, this prerequisite is not always satisfied. In this case, the correlation-based methods are not feasible. Actually, the acquired signals contain the characteristics related to the acoustic propagation channels; thus the blind system identification strategy is applied to estimate the transmission performances of acoustic channels. Then the times due to the propagation of the leak source signal travelling from the leak point to sensors are determined. In this way, for leak location, the detection distance is no longer a prerequisite. In blind system identification, due to the long impulse responses of the leak acoustic channels, the channels are inevitably ill conditioned and sensitive to the initial values. To overcome the ill conditions, the overlap-save and cross-correlation fitting techniques are utilized to identify the long impulse sequences under a built constraint. In order to avoid converging to the local minima, the genetic algorithm is used to minimize the cost functions. The practical detection results show the validity of the proposed scheme.

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Sensor-fusion of hydraulic data for burst detection and location in a treated water distribution system

et al. 2003

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Low-cost failure sensor design and development for water pipeline distribution systems

Cited by 3 publications

References 1 publication

Modeling of Hydraulic Load of Electric Drive in Electrical Complex of Pumping Station

Modeling of Hydraulic Load of Electric Drive in Electrical Complex of Pumping Station

The genetic-algorithm-enhanced blind system identification for water distribution pipeline leak detection

Sensor-fusion of hydraulic data for burst detection and location in a treated water distribution system

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