Fuzzy sets analysis for leak detection in infrastructure systems: a proposed methodology

Mamlook, Rustom; Al-Jayyousi, Odeh

doi:10.1007/s10098-003-0209-8

Cited by 38 publications

(12 citation statements)

References 15 publications

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“…Also, Fuzzy methodology has been utilized for evaluation purposes; it has been used for evaluation of factors that affect the solar still production, energy conservation programs in residential sector, and the parameters that affect leakage in infrastructure systems (Mamlook and Badran 2006;Jaber et al 2005;Mamlook and Al-Jayyousi 2003).…”

Section: Fuzzy Methodologymentioning

confidence: 99%

Toward clean environment: evaluation of solar electric power technologies using fuzzy logic

Badran

Mamlook

Abdulhadi

2011

Clean Techn Environ Policy

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The rapid expansion of the use of solar energy power plants worldwide is a subject that is being followed with interest. Fuzzy logic methodology is used for evaluating the solar thermal power technology, it compresses huge amount of data into smaller sets, and it has the ability to decide between different solar technologies on the basis of their benefits and costs. The most often considered solar technologies were parabolic trough, central receiver, dish sterling engine, compact linear Fresnel reflector (CLFR), solar chimney, photovoltaic (PV), and solar pond. The aim of our research is to provide the needed information to make a judgment or a decision of adopting the most preferred solar technology in terms of installation and development using fuzzy set methodology. The criteria of the evaluation were based on different parameters, i.e., power capacity, efficiency, availability, capacity factor, storage capability, cost, maturity, water usage, land usage, and safety. The key barriers and features for each technology on the basis of benefit-to-cost ratios are addressed. The results showed that CLFR was found to be the best choice in terms of research, development, and implementation, followed by parabolic trough technology, then the central receiver technology, dish sterling engine, solar chimney, PV, and solar pond, according to the order of preference.

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Section: Fuzzy Methodologymentioning

confidence: 99%

Toward clean environment: evaluation of solar electric power technologies using fuzzy logic

Badran

Mamlook

Abdulhadi

2011

Clean Techn Environ Policy

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“…The application of the fuzzy set methodology offers reasonable prediction and assessment for leakage in systems [10]. The various characteristics for each case study are converted into relative weights using the fuzzy set method.…”

Section: Spe-174405-msmentioning

confidence: 99%

Continuous Environmentally Efficient Pipeline Leak Detection

et al. 2015

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High-resolution sensors provide essential information to the oil and gas industry when planning for corridor right-of-way, land restoration, damage prevention, risk management and emergency response/ damage prevention. The world's growing need for energy has put pressure on the remote sensing community to create even higher resolution and more accurate sensors than ever before. The location of the area of interest where remote sensing is needed is often based on the location of potential petroleum reserves. Political, terrain and weather conditions often determine the choice of technology used to collect the necessary data. Continuous pipeline monitoring is becoming increasingly critical for the oil and gas industry, which faces new challenges due to higher demands for energy. This paper presents the design, development and testing of a smart, wireless sensor network for early leak detection in oil pipelines, based on sensor measurements. Today's low power sensors are capable of measuring pressure, temperature and flow changes due to leaks. We describe a system model for determining decision-making strategies based upon the ability to perform data mining and pattern discovery by utilizing sensor information to detect leaks or abnormal situations. We discuss the development of a method for determining actionable information using game theory. We focus on applying probabilistic models to leak detection and geospatial tools for assisting emergency response and pipeline repairs. Probabilistic predictions are critical in practice on many decision-making applications. However, applicability to big data is complicated by the difficulties of inference in complex probabilistic models, and by computational constraints.

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“…Thus, pressure control might be needed to minimise the leakage outflow through these nodes as well as the overall leakage in the network. The pipes connected to these nodes include pipes (4,5,59,60,70,71) for node 5, pipes (5,6,14,46,60,61,71) for node 6, and pies (51,52,53) to node 41 respectively. Any pipe connected to these nodes with a relatively high leakage flow rate requires a pressure control at either one or both of its end nodes.…”

Section: Numerical Examplesmentioning

confidence: 99%

“…In some well-developed and monitored water distribution systems, about 7% of the total input volume into the network is lost through leaking pipes [2]. Elsewhere, in less monitored systems, more than 50% of the total input volume into the network is lost through leaking pipes [3,4]. Therefore, water loss through leaking pipes constitutes a major challenge to the operational services of water utilities and is recognised as a costly problem strongly linked with interrupted service, waste of energy and natural resources [5][6][7].…”

Section: Introductionmentioning

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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Fuzzy sets analysis for leak detection in infrastructure systems: a proposed methodology

Cited by 38 publications

References 15 publications

Toward clean environment: evaluation of solar electric power technologies using fuzzy logic

Toward clean environment: evaluation of solar electric power technologies using fuzzy logic

Continuous Environmentally Efficient Pipeline Leak Detection

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

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