Special Issue "Sensors for Fluid Leak Detection"

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (15 March 2014)

Special Issue Editor

Guest Editor
Prof. Dr. Gonzalo Pajares Martinsanz
Dpt. Software Engineering and Artificial Intelligence, Faculty of Informatics, University Complutense of Madrid, 28040 Madrid, Spain
E-Mail: pajares@fdi.ucm.es
Interests: computer vision; image processing; pattern recognition; 3D image reconstruction, spatio-temporal image change detection and track movement; fusion and registering from imaging sensors; superresolution from low-resolution image sensors

Special Issue Information

Dear Colleagues,

Fluid leak detection is a very old problem, gas or water leaks in aerial pipes or underground pipelines are typical examples. Detection of other fluid leaks has attracted less. This is the case of early oil detection, particularly in underwater sea-lines or other chemical products.

Growing technological development of sensors, for fluid leaks detection, has greater chances of success particularly in early stages. Sometimes, sensors must be installed on multisensory platforms where leak detection is a problem but also the positioning and platform navigation. This is the case of underwater or ground vehicles exploring sea-lines or industrial plants.

This special issue is devoted to sensors devices, materials, technologies and tools for fluid leak detection in different environments such as underwater sea-lines, spillage on the sea surface or ground and aerial pipelines in buildings or industrial plants. Physical and chemical sensors or biosensors are to be considered.

These sensors could also be used as an aid for other purposes such as navigation or positioning of autonomous or remotely operated vehicles (underwater, surface, ground) under the leak detection context.

Prof. Dr. Gonzalo Pajares Martinsanz
Guest Editor

Submission

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed Open Access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs).


Published Papers (7 papers)

Sensors 2014, 14(3), 5595-5610; doi:10.3390/s140305595
Received: 25 November 2013; in revised form: 23 December 2013 / Accepted: 2 January 2014 / Published: 20 March 2014
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Sensors 2014, 14(2), 3557-3577; doi:10.3390/s140203557
Received: 29 October 2013; in revised form: 27 January 2014 / Accepted: 7 February 2014 / Published: 20 February 2014
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Sensors 2013, 13(12), 17057-17066; doi:10.3390/s131217057
Received: 25 October 2013; in revised form: 2 December 2013 / Accepted: 9 December 2013 / Published: 11 December 2013
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Sensors 2013, 13(12), 15912-15936; doi:10.3390/s131215912
Received: 17 September 2013; in revised form: 30 October 2013 / Accepted: 11 November 2013 / Published: 25 November 2013
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Sensors 2013, 13(11), 14984-15005; doi:10.3390/s131114984
Received: 5 August 2013; in revised form: 19 October 2013 / Accepted: 23 October 2013 / Published: 4 November 2013
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Sensors 2013, 13(10), 13560-13574; doi:10.3390/s131013560
Received: 31 July 2013; in revised form: 23 September 2013 / Accepted: 27 September 2013 / Published: 9 October 2013
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Sensors 2013, 13(9), 11522-11538; doi:10.3390/s130911522
Received: 13 June 2013; in revised form: 26 August 2013 / Accepted: 27 August 2013 / Published: 2 September 2013
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Type of Paper: Article
Title:
GPR-Based Water Leak Models in Water Distribution Systems
Authors:
David Ayala-Cabrera 1, Manuel Herrera 2, Joaquín Izquierdo 1, Silvia J. Ocaña-Levario 1 and Rafael Pérez-García 1
Affiliations: 1 FluIng-IMM, Universitat Politècnica de València, Valencia, Spain; E-Mail: jizquier@upv.es
2 BATir, Université libre de Bruxelles, Brussels, Belgium
Abstract: Water is not only of great value, but also challenging to manage. It has been calculated that many water distribution systems (WDSs) around the world lose more than 40 percent of the clean water pumped into the distribution system because of leaks before that water reaches end consumers. By reducing the amount of water leaked, WDS managers can reduce the amount of money wasted on producing water, consuming energy required to pump water and treating water for distribution, can increase system reliability, and can satisfy consumer needs. Having access to sufficient information regarding leaks is a complex task. Many water utilities struggle to even measure and locate leaks in their distribution networks. So, improved leakage management in WDSs is one of the intelligent solutions that can make a difference. The use of different types of smart sensors to gather data and the application of advanced analytics could provide valuable information on the location of leaks in the network. Specifically, non destructive methods, such as ground penetrating radar (GPR), can contribute to locate primordial leaks, thus to help resolve the problem within an integral strategy, while avoiding social and economical costs. In this work we evaluate the feasibility of implementing one such strategy. The first step includes a series of lab tests to create a suitable database of GPR radargrams. Then, the relevant characteristics are extracted by interpreting those images using various statistical, KDD and multi-agent tools. The final step involves the generation of models that enable intelligent, automatic interpretation and, as a result, leak detection when the models are fed with field radargrams. This tool intends to represent a big opportunity to improve utility performance.

Type of Paper: Article
Title:
Microseismic Monitoring of CO2 Injection at the Penn West EOR Pilot, Canada
Authors: P. Martínez-Garzón 1, M. Bohnhoff 1, G. Kwiatek 1, G. Zambrano-Narváez 2 and R. Chalaturnyk 2
Affiliations: 1 Department of Geomechanics and Rheology, Telegrafenberg Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany
2 Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Canada; E-Mail: patricia@gfz-potsdam.de
Abstract: A passive seismic monitoring campaign was carried out in the frame of a CO2 – EOR pilot project in Alberta, Canada. Our analysis focuses on a two-week period during which prominent downhole pressure fluctuations in the reservoir were accompanied by leakage of CO2 and CH4 along the monitoring well that was equipped with an array of short-period borehole geophones. We applied several state of the art seismological processing schemes to the continuous seismic waveform recordings. During the period analysed here we did not find evidence for seismic signatures that can be associated with microseismic events. Instead, we identified signals related to the leakage of CO2 and CH4, in that seven out of the eight geophones do show a clear elevated noise level. Our results confirm that microseismic monitoring of reservoir treatment can contribute towards improved reservoir and leakage monitoring.

Type of Paper: Article
Title:
Inverse Transient Analysis for Classification of Wall Thickness Variations in Pipelines
Authors: Jeffrey Tuck and Pedro Lee
Affiliation: Department of Civil and Natural Resources Engineering, University of Canterbury, New Zealand; E-Mails: jeff.tuck@pg.canterbury.ac.nz (J.T.); pedro.lee@canterbury.ac.nz (P.L.)
Abstract: Analysis of transient fluid pressure signals has been investigated as an alternative method of leak and fault detection in pipeline systems and has shown promise in laboratory and field trials. The advantages of the method are that it can potentially provide a quick and cost effective means to locate faults in a pipeline while the system remains fully operational. The only requirement being that high speed pressure sensors are placed in contact with the fluid. Further development of the method requires detailed numerical models and understanding of transient flow within a pipeline where variations in pipeline condition and geometry occur. One such variation commonly encountered in a pipeline with leaks or susceptible to leak development is degradation and thinning of pipe walls. This paper aims to improve transient based fault detection methods by investigating how changes in pipe wall thickness will affect the transient behaviour of a system through analysis of laboratory experiments. The laboratory experiment is carried out on a stainless steel pipeline where a pipe section is inserted which has a change in wall thickness while maintaining an equivalent outside diameter. In order to detect the location and severity of these changes in wall conditions within the laboratory system an inverse transient analysis procedure is employed which considers independent variations in wavespeed and diameter. Inverse transient analyses are carried out using a genetic algorithm optimisation routine to match the response from a one-dimensional method of characteristics transient model to the experimental time domain pressure responses. The accuracy of the detection technique is evaluated and benefits associated with various simplifying assumptions and simulation run times are investigated. It is found that for the case investigated, changes in the wavespeed and nominal diameter of the pipeline are both important to the accuracy of the inverse analysis procedure and can be used to differentiate transient behaviour caused by changes in wall thickness from that caused by other known faults such as leaks. Further application of the method to real pipelines is discussed.

Type of Paper: Article
Title: Passive Electrical Monitoring and Localization of Leakages in Wells
Authors: A. Revil and A. Haas
Affiliations: Colorado School of Mines, Dept of Geophysics, 1500 Illinois street, 80401 Golden CO, USA; E-Mail: arevil@mines.edu
Abstract: We demonstrate that electrical fields of electrokinetic nature (i.e., associated with the flow of the pore water)
and associated with leakages from wells can be measured remotely. The technique is similar to what is performed in electroencephalography. We developed a set of laboratory experiments showing how the electrical fields can be recorded using a research-grade medical electroencephalograph and inverted to localize the causative source of electrical current and therefore localize the leak. We can also used this technique to monitor how the leak evolves over time.

Type of Paper: Article
Title: Leak Detection in Complex Waterworks: Increasing Qualitative Expression Using a Multidimensional Model
Authors: Aimé Lay-Ekuakille, Giuseppe Griffo and Patrizia Vergallo
Affiliation: Department of Innovation Engineering, University of Salento, Lecce, Italy; E-Mail: aime.lay.ekuakille@unisalento.it
Abstract: Spectral analysis method is one of the most important approaches in determining the location of leaks in pipelines. It is based on processing signals from sensors located on the pipelines or from other devices and instruments.  Fast Fourier transform (FFT) technique is generally used for this purposes. But the accuracy in detecting leaks can be increased thanks to the use of other transforms that overcome FFT limitations.  FDM (Filter Diagonalization Method), one of them, displays better results than FFT ones as it is shown in this work.  The paper presents the application of one-dimensional FDM to be compared to two-dimensional FDM. Both algorithms have been used on a real experimental zigzag plant.  The multidimensional approach, by means of 2D FDM, allows to notice, in many cases, an extended area gathering different side peaks with respect to the main peak that is surely seen in 1D FDM.  While 1D FDM exhibits extraordinary results by increasing the accuracy, 2D FDM reveal peaks of the same leak that permit to better understand the nature of leaks correlated to the frequency of signals delivered by the sensors which a magnetic one, and located on a pipeline.

Type of Paper: Article
Title: A Comparison between Decimated Padé Approximant and Decimated Signal Diagonalization Methods for Leak Detection Pipelines
Authors: Aimé Lay-Ekuakille, Giuseppe Griffo and Patrizia Vergallo
Affiliation: Department of Innovation Engineering, University of Salento, Lecce, Italy; E-Mail: aime.lay.ekuakille@unisalento.it
Abstract: Quick localization and processing huge signals are two basic aspects in leak detection as well as uncertainty of leakage position. The aforementioned aspects become critical for complex and interlaced waterworks, so common and even advanced  algorithms, dedicated for spectral estimates, are not always able to deliver expected results. Two interesting algorithms used in NMR (nuclear magnetic resonance) and ICR (ion cyclotron resonance) are used and compared each other, they are DPA (Decimated Padé Approximant) and DSD (Decimated Signal Diagonalization). The major characteristic of DPA is windowing since it allows to split the initial problem into smaller size subproblems; the ill conditioning and the presence of extraneous spectral components take place when the rank of the matrix, equal to the number of true spectral components, is greater than its size. Conversely, for DSD, even the use of windowing technique is envisaged, it is a powerful technique exhibiting a better resolution than FDM (Filter Diagonalization Method). Hence, in some circumstances, it could be better to work with both algorithms finding a compromise between processing time and resolution.

Last update: 3 February 2014

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