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Author: Fei Yang
Publisher:
ISBN:
Category : Leak detectors
Languages : en
Pages : 62
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Book Description
Modern cities can no longer tolerate insufficiencies in water supply systems. Of the many options available for conserving water, detecting a leakage from a sealed pipe is an effective low cost method. The quality of the leak detection system is determined by accuracy. The aims of this study were developing a system to minimize the probability of false alarm and misdetection, and to detect the leak in time by using a multi-sensor network. Cross correlation and the Artificial Neural Network (ANN) algorithm were utilized to pinpoint the leak location. The results showed that the probabilities of false alarm and miss detection have been decreased. In addition, an analysis of the results in leak localization implies that the error of estimated location and physical location decreases if more data is fed to the ANN algorithm and it finally stabilizes within ±27.22 mm. The results of this study are presented such that they can be used as an aid to a water pipeline monitoring system.
Author: Fei Yang
Publisher:
ISBN:
Category : Leak detectors
Languages : en
Pages : 62
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Book Description
Modern cities can no longer tolerate insufficiencies in water supply systems. Of the many options available for conserving water, detecting a leakage from a sealed pipe is an effective low cost method. The quality of the leak detection system is determined by accuracy. The aims of this study were developing a system to minimize the probability of false alarm and misdetection, and to detect the leak in time by using a multi-sensor network. Cross correlation and the Artificial Neural Network (ANN) algorithm were utilized to pinpoint the leak location. The results showed that the probabilities of false alarm and miss detection have been decreased. In addition, an analysis of the results in leak localization implies that the error of estimated location and physical location decreases if more data is fed to the ANN algorithm and it finally stabilizes within ±27.22 mm. The results of this study are presented such that they can be used as an aid to a water pipeline monitoring system.
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: Samer El-Zahab
Publisher:
ISBN:
Category :
Languages : en
Pages : 238
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Book Description
Today, 844 million humans around the world have no access to safe drinking water. Furthermore, every 90 seconds, one child dies from water-related illnesses. Major cities lose 15% - 50% of their water and, in some cases, losses may reach up to 70%, mostly due to leaks. Therefore, it is paramount to preserve water as an invaluable resource through water networks, particularly in large cities in which leak repair may cause disruption. Municipalities usually tackle leak problems using various detection systems and technologies, often long after leaks occur; however, such efforts are not enough to detect leaks at early stages. Therefore, the main objectives of the present research are to develop and validate a leak detection system and to optimize leak repair prioritization. The development of the leak detection models goes through several phases: (1) technology and device selection, (2) experimental work, (3) signal analysis, (4) selection of parameters, (5) machine learning model development and (6) validation of developed models. To detect leaks, vibration signals are collected through a variety of controlled experiments on PVC and ductile iron pipelines using wireless accelerometers, i.e., micro-electronic mechanical sensors (MEMS). The signals are analyzed to pinpoint leaks in water pipelines. Similarly, acoustic signals are collected from a pilot project in the city of Montreal, using noise loggers as another detection technology. The collected signals are also analyzed to detect and pinpoint the leaks. The leak detection system has presented promising results using both technologies. The developed MEMS model is capable of accurately pinpointing leaks within 12 centimeters from the exact location. Comparatively, for noise loggers, the developed model can detect the exact leak location within a 25-cm radius for an actual leak. The leak repair prioritization model uses two optimization techniques: (1) a well-known genetic algorithm and (2) a newly innovative Lazy Serpent Algorithm that is developed in the present research. The Lazy Serpent Algorithm has proved capable of surpassing the genetic algorithm in determining a more optimal schedule using much less computation time. The developed research proves that automated real-time leak detection is possible and can help governments save water resource and funds. The developed research proves the viability of accelerometers as a standalone leak detection technology and opens the door for further research and experimentations. The leak detection system model helps municipalities and water resource agencies rapidly detect leaks when they occur in real-time. The developed pinpointing models facilitate the leak repair process by precisely determine the leak location where the repair works should be conducted. The Lazy Serpent Algorithm helps municipalities better distribute their resources to maximize their desired benefits.
Author: Eugen Ruus
Publisher: Kelowna, B.C. : Ruus Consulting
ISBN: 9781550565171
Category : Hydraulic transients
Languages : en
Pages : 325
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Book Description
Author: Peter Pifu Zhang
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Author: B. H. Shakmak
Publisher:
ISBN:
Category :
Languages : en
Pages :
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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: Mohammadamin Jahanpour
Publisher:
ISBN:
Category : Leak detectors
Languages : en
Pages : 140
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Book Description
Leakages in concealed pipes in urban water distribution systems (WDS) can cause losses of up to 25% of potable water supply in municipalities. These losses are not only a tremendous waste of water but also the energy spent to treat and distribute it. Techniques for leak detection and localization in WDS have evolved considerably since the mid-1950s. Among these methods, model-based leak diagnosis methods (MFD) have been extensively studied in the literature, as they are more economical compared to others. MFD methods infer the existence and position of leaks based on continuously monitoring pressure levels in the WDS and comparing these to the expected values obtained from simulating a calibrated hydraulic model of the WDS. In the event of an anomaly (e.g., a leak), the sampled pressure levels (measured by the sensors) should significantly deviate from expected values which are obtained by simulation under an assumed no-leak condition. Although the methodology is efficient in terms of the number of required sensors and operational person-hours, it is at risk of failing to distinguish between the effect of leaks and water demand variations. This is because both leaks and demand fluctuations have a similar change on pressure levels along the network. This study aims to improve the robustness of the MFD method by explicitly considering the uncertainty in the nodal demands across the WDS. The influence of demand uncertainty on nodal pressure is analyzed by generating model-based system responses that are time-variable and conditional on known data (e.g., total demand across the WDS). Monte Carlo methods are used to generate conditional realizations of spatially variable sets of nodal demands such that simulated states match the available observed system states at the time any pressure observation is sampled. After characterizing the distributions of expected nodal pressures under the no-leak condition, a statistical detection test is defined that asserts the existence of a leak based on evidence from comparing the observations with their corresponding distributions. The performance of the proposed detection analysis is then evaluated in response to multiple synthetic leak and no-leak scenarios. To fine-tune the configuration of the detection test design parameters, its performance is evaluated by computing the false positive and false negative rates across the leak and no-leak scenarios. These two metrics are utilized to solve the sensor placement optimization problem as a multi-objective optimization problem. Results in two synthetic WDS case studies show that under the most influential source of uncertainty in WDS modelling (nodal demands), the proposed detection test functions well and multi-objective optimization can lead to robust sensor placement and other valuable insights.
Author: Guang-Zhong Yang
Publisher: Springer
ISBN: 1447163745
Category : Computers
Languages : en
Pages : 572
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Book Description
The last decade has witnessed a rapid surge of interest in new sensing and monitoring devices for wellbeing and healthcare. One key development in this area is wireless, wearable and implantable in vivo monitoring and intervention. A myriad of platforms are now available from both academic institutions and commercial organisations. They permit the management of patients with both acute and chronic symptoms, including diabetes, cardiovascular diseases, treatment of epilepsy and other debilitating neurological disorders. Despite extensive developments in sensing technologies, there are significant research issues related to system integration, sensor miniaturisation, low-power sensor interface, wireless telemetry and signal processing. In the 2nd edition of this popular and authoritative reference on Body Sensor Networks (BSN), major topics related to the latest technological developments and potential clinical applications are discussed, with contents covering. Biosensor Design, Interfacing and Nanotechnology Wireless Communication and Network Topologies Communication Protocols and Standards Energy Harvesting and Power Delivery Ultra-low Power Bio-inspired Processing Multi-sensor Fusion and Context Aware Sensing Autonomic Sensing Wearable, Ingestible Sensor Integration and Exemplar Applications System Integration and Wireless Sensor Microsystems The book also provides a comprehensive review of the current wireless sensor development platforms and a step-by-step guide to developing your own BSN applications through the use of the BSN development kit.
Author: David Hall
Publisher: CRC Press
ISBN: 1420038540
Category : Technology & Engineering
Languages : en
Pages : 564
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Book Description
The emerging technology of multisensor data fusion has a wide range of applications, both in Department of Defense (DoD) areas and in the civilian arena. The techniques of multisensor data fusion draw from an equally broad range of disciplines, including artificial intelligence, pattern recognition, and statistical estimation. With the rapid evolut
