Robust Leak Localization in Water Distribution Networks Using Machine Learning Techniques PDF Download
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Author: Adrià Soldevila Coma
Publisher:
ISBN:
Category :
Languages : en
Pages : 189
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Book Description
Author: Adrià Soldevila Coma
Publisher:
ISBN:
Category :
Languages : en
Pages : 189
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Book Description
Author: Neda Mashhadi
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This manuscript presents the results of research about the use of the Artificial Intelligence moths to detect and localize leaks in the water distribution networks. The manuscript is organized in three chapters:The first chapter includes a literature review about the leak in the water distribution networks. First, it presents first the origin of the water leak and its dramatic economic, social and environmental impact. Then, it presents the conventional methods used for the detection of the water leak including hardware-based and software-based methods. This chapter highlights the opportunities offered by the smart monitoring and the Artificial Intelligence methods for the detection of leaks in the water networks. It also shows a need to explore on the same example the capacity of the main AI methods to detect and localize leaks in complex water networks.The second chapter presents the water network of the scientific campus of Lille University, which is used as a support for this research. It argues the selection of this campus by its representativity of a small town, the complexity of the water network and the availability of data about the water network asset and consumption. The chapter also presents the construction of a Lab pilot to investigate of the possibility to localize water leaks from the ratios of the water supply flow rates.The third chapter presents a synthesis of the use of Machine Learning methods in leak localization. It also presents the use of the software EPANET for the generation of data including the impact of 215 individual and double leaks on the variation of the water supply flow rates and the pressure in five zones of the campus. These data are then used to investigate the capacity of five Machine Learning methods to localize leaks in the water distribution system. The chapter suggests some recommendations for the use of ML methods in water leak localization.
Author: M. Farley
Publisher: IWA Publishing
ISBN: 1900222116
Category : Science
Languages : en
Pages : 297
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Book Description
This is a best practice manual for addressing water losses in water distribution networks worldwide. Systems and methodologies are presented for improving water loss and leakage management in a range of networks, from systems with a well-developed infrastructure to those in developing countries where the network may need to be upgraded. The key feature of the manual is a diagnostic approach to develop a water loss strategy - using the appropriate tools to find the right solutions - which can be applied to any network. The methods of assessing the scale and volume of water loss are outlined, together with the procedures for setting up leakage monitoring and detection systems. As well as real losses (leakage) procedures for addressing apparent losses, by introducing regulatory and customer metering policies are explained. Suggestions are made for demand management and water conservation programmes, to complement the water loss strategy. Recommendations are made for training workshops and operation and maintenance programmes to ensure skills transfer and sustainability. The manual is illustrated throughout with case studies. Losses in Water Distribution Networks will appeal to a wide range of practitioners responsible for designing and managing a water loss strategy. These include consultants, operations managers, engineers, technicians and operational staff. It will also be a valuable reference for senior managers and decision makers, who may require an overview of the principles and procedures for controlling losses. The book will also be suitable as a source document for courses in Water Engineering, Resource Management and Environmental Management.
Author: Vicenç Puig
Publisher: Springer
ISBN: 3319507516
Category : Technology & Engineering
Languages : en
Pages : 438
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Book Description
This book presents a set of approaches for the real-time monitoring and control of drinking-water networks based on advanced information and communication technologies. It shows the reader how to achieve significant improvements in efficiency in terms of water use, energy consumption, water loss minimization, and water quality guarantees. The methods and approaches presented are illustrated and have been applied using real-life pilot demonstrations based on the drinking-water network in Barcelona, Spain. The proposed approaches and tools cover: • decision-making support for real-time optimal control of water transport networks, explaining how stochastic model predictive control algorithms that take explicit account of uncertainties associated with energy prices and real demand allow the main flow and pressure actuators—pumping stations and pressure regulation valves— and intermediate storage tanks to be operated to meet demand using the most sustainable types of source and with minimum electricity costs;• decision-making support for monitoring water balance and distribution network quality in real time, implementing fault detection and diagnosis techniques and using information from hundreds of flow, pressure, and water-quality sensors together with hydraulic and quality-parameter-evolution models to detect and locate leaks in the network, possible breaches in water quality, and failures in sensors and/or actuators;• consumer-demand prediction, based on smart metering techniques, producing detailed analyses and forecasts of consumption patterns, providing a customer communications service, and suggesting economic measures intended to promote more efficient use of water at the household level. Researchers and engineers working with drinking-water networks will find this a vital support in overcoming the problems associated with increased population, environmental sensitivities and regulation, aging infrastructures, energy requirements, and limited water sources.
Author: Stuart Hamilton
Publisher: IWA Publishing
ISBN: 1780404700
Category : Science
Languages : en
Pages : 106
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Book Description
Ageing infrastructure and declining water resources are major concerns with a growing global population. Controlling water loss has therefore become a priority for water utilities around the world. In order to improve efficiencies, water utilities need to apply good practices in leak detection. Leak Detection: Technology and Implementation assists water utilities with the development and implementation of leak detection programs. Leak detection and repair is one of the components of controlling water loss. In addition, techniques are discussed within this book and relevant case studies are presented. This book provides useful and practical information on leakage issues.
Author: American Water Works Association
Publisher: American Water Works Association
ISBN: 1583216316
Category : Science
Languages : en
Pages : 303
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Book Description
In this handbook readers will find industry-approved procedures for water utilities to conduct systemwide water audits to assess real and apparent distribution-system water losses, recover lost revenue, and detect and repair pipe leaks.
Author: Joseph Cornelius Van der Walt
Publisher:
ISBN:
Category :
Languages : en
Pages : 216
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Book Description
In 2012, the National Non-Revenue Water assessment revealed that South Africa has 37% of non-revenue water. With the steadily growing demand for this scarce resource, the detection of leaks in pipe networks is becoming more important. Currently, in South Africa the primary method of detecting leaks is to install pressure management systems and monitoring minimum night time ows [1]. The pressure- ow deviation method, can be used to formulate an inverse analysis model based leak detection problem. This problem can then be solved using Arti cial Neural Networks, Support Vector Machines and other optimization methods. With EPANET, di erent networks were tested to compare these methods to nding leaks, using an inverse analysis formulated problem. Four di erent numerical networks were modeled and tested, a simple single pipe network, a small agricultural site, a distribution network proposed and investigated by Poulakis et al. [2] and the simulated model of the experimental network that was designed and commissioned during the study in our laboratory. From the numerical investigation, it was found that the optimization methods struggled to nd solutions for simple networks with in nite number of solutions for the problem. For more complex numerical networks, it was seen that the Support Vector machine and the Arti cial Neural Networks trained to the averages of their respective data sets. Errors to ensure an accurate solution found by these algorithms were calculated as 2:6% for the numerical experimental network. The experimental network consisted of six possible leaking pipes, each having a length of 3m and a diameter of 10mm. Three leak cases were tested with diameters of 3mm and 2mm. Overall, the Support Vector machine could locate the leaking pipe with the best accuracy, while the minimizing of non-regularized error could calculate the size and location of the leak the most accurately. Multiple leak cases were measured with the experimental network. The Support Vector machine was tested on these measurements, where it was found that two of the three leak cases could be solved with relative accuracies. Sensor usage optimization was completed on the measurements for the experimental network, where it was found that the leaks could be classi ed correctly with probabilities higher than 98% if only two sensors were used in the training of the SVM instead of all twelve. Overall this method of leak detection shows promise for certain applications in the future. With practical applications on water distribution, transportation, and agricultural networks.
Author: Sandro Skansi
Publisher: Springer
ISBN: 3319730045
Category : Computers
Languages : en
Pages : 196
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Book Description
This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive style, explaining the mathematical derivations in a step-by-step manner. The content coverage includes convolutional networks, LSTMs, Word2vec, RBMs, DBNs, neural Turing machines, memory networks and autoencoders. Numerous examples in working Python code are provided throughout the book, and the code is also supplied separately at an accompanying website. Topics and features: introduces the fundamentals of machine learning, and the mathematical and computational prerequisites for deep learning; discusses feed-forward neural networks, and explores the modifications to these which can be applied to any neural network; examines convolutional neural networks, and the recurrent connections to a feed-forward neural network; describes the notion of distributed representations, the concept of the autoencoder, and the ideas behind language processing with deep learning; presents a brief history of artificial intelligence and neural networks, and reviews interesting open research problems in deep learning and connectionism. This clearly written and lively primer on deep learning is essential reading for graduate and advanced undergraduate students of computer science, cognitive science and mathematics, as well as fields such as linguistics, logic, philosophy, and psychology.
Author: Giuseppe Pezzinga
Publisher: MDPI
ISBN: 3038975567
Category : Technology & Engineering
Languages : en
Pages : 174
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Book Description
The Special Issue on Advances in Water Distribution Networks (WDNs) explores four important topics of research in the framework of WDNs, namely simulation and optimization modelling, topology and partitioning, water quality, and service effectiveness. With regard to the first topic, the following aspects are addressed: pressure-driven formulations, algorithms for the optimal location of control valves to minimize leakage, the benefits of water discharge prediction for the remote real time control of valves, and transients generated by pumps operating as turbines. In the context of the second topic, a topological taxonomy of WDNs is presented, and partitioning methods for the creation of district metered areas are compared. In relation to the third topic, the vulnerability to trihalomethane is assessed, and a statistical optimization model to minimize heavy metal releases is presented. Finally, the fourth topic focusses on the estimation of non-revenue water, including leakage and unauthorized consumption, and on the assessment of service under intermittent supply conditions.
Author: Eleni N. Chatzi
Publisher: Frontiers Media SA
ISBN: 2889660885
Category : Technology & Engineering
Languages : en
Pages : 208
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Book Description
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
