scholarly journals Model-based leak detection and location in water distribution networks considering an extended-horizon analysis of pressure sensitivities

2013 ◽  
Vol 16 (3) ◽  
pp. 649-670 ◽  
Author(s):  
Myrna V. Casillas Ponce ◽  
Luis E. Garza Castañón ◽  
Vicenç Puig Cayuela
Keyword(s):  
Water Distribution ◽  
Real Data ◽  
Leak Detection ◽  
Distribution Networks ◽  
Optimization Method ◽  
Least Square ◽  
Water Distribution Networks ◽  
Sensitivity Matrix ◽  
Model Based ◽  
Leak Detection And Location

In this paper, we propose a new approach for model-based leak detection and location in water distribution networks (WDN), which considers an extended time-horizon analysis of pressure sensitivities. Five different ways of using the leak sensitivity matrix to isolate the leaks are described and compared. The first method is based on the binarization approach. The second, third and fourth methods are based on the comparison of the measured pressure vectors with the leak sensitivity matrix using different metrics: correlation, angle between vectors and Euclidean distance, respectively. The fifth method is based on the least square optimization method. The performance of these methods is compared when applied to two academic small networks (Hanoi and Quebra) widely used in the literature. Finally, the three methods with better performance are applied to a district metering area of the Barcelona WDN using real data.

scholarly journals An Unsupervised Approach to Leak Detection and Location in Water Distribution Networks

2018 ◽  
Vol 28 (2) ◽  
pp. 283-295 ◽  
Author(s):  
Marcos Quiñones-Grueiro ◽  
Cristina Verde ◽  
Alberto Prieto-Moreno ◽  
Orestes Llanes-Santiago
Keyword(s):  
Water Distribution ◽  
Pressure Sensors ◽  
Leak Detection ◽  
Distribution Networks ◽  
Water Distribution Networks ◽  
Normal Operation ◽  
Time Interval ◽  
Classification Rate ◽  
Unsupervised Approach ◽  
Leak Detection And Location

Abstract The water loss detection and location problem has received great attention in recent years. In particular, data-driven methods have shown very promising results mainly because they can deal with uncertain data and the variability of models better than model-based methods. The main contribution of this work is an unsupervised approach to leak detection and location in water distribution networks. This approach is based on a zone division of the network, and it only requires data from a normal operation scenario of the pipe network. The proposition combines a periodic transformation and a data vector extension together with principal component analysis of leak detection. A reconstruction-based contribution index is used for determining the leak zone location. The Hanoi distribution network is employed as the case study for illustrating the feasibility of the proposal. Single leaks are emulated with varying outflow magnitudes at all nodes that represent less than 2.5% of the total demand of the network and between 3% and 25% of the node’s demand. All leaks can be detected within the time interval of a day, and the average classification rate obtained is 85.28% by using only data from three pressure sensors.

scholarly journals Extended-Horizon Analysis of Pressure Sensitivities for Leak Detection in Water Distribution Networks

2012 ◽  
Vol 45 (20) ◽  
pp. 570-575 ◽  
Author(s):  
Myrna Violeta Casillas Ponce ◽  
Luis Eduardo Garza Castañón, ◽  
Vicenç Puig Cayuela
Keyword(s):  
Water Distribution ◽  
Leak Detection ◽  
Distribution Networks ◽  
Water Distribution Networks

scholarly journals Sensor placement for leak detection and location in water distribution networks

2014 ◽  
Vol 14 (5) ◽  
pp. 795-803 ◽  
Author(s):  
R. Sarrate ◽  
J. Blesa ◽  
F. Nejjari ◽  
J. Quevedo
Keyword(s):  
Water Distribution ◽  
Structural Model ◽  
Distribution Network ◽  
Pressure Sensors ◽  
Water Distribution Network ◽  
Leak Detection ◽  
Distribution Networks ◽  
Optimization Strategy ◽  
Sensor Configuration ◽  
Leak Detection And Location

The performance of a leak detection and location algorithm depends on the set of measurements that are available in the network. This work presents an optimization strategy that maximizes the leak diagnosability performance of the network. The goal is to characterize and determine a sensor configuration that guarantees a maximum degree of diagnosability while the sensor configuration cost satisfies a budgetary constraint. To efficiently handle the complexity of the distribution network an efficient branch and bound search strategy based on a structural model is used. However, in order to reduce even more the size and the complexity of the problem the present work proposes to combine this methodology with clustering techniques. The strategy developed in this work is successfully applied to determine the optimal set of pressure sensors that should be installed in a District Metered Area in the Barcelona water distribution network.

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