Optimal Sensor Placement for Leak Location in Water Distribution Networks using Evolutionary Algorithms (original) (raw)
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Sensor Placement for Leak Location in Water Distribution Networks using the Leak Signature Space
IFAC-PapersOnLine, 2015
In this paper, a sensor placement approach to improve the leak location in water distribution networks is proposed. The sensor placement problem is formulated as an integer optimization problem where the criterion to minimize is the number of overlapping signature domains computed from the leak signature space (LSS) representation. A stochastic optimization process is proposed to solve this problem, based on either a Genetic Algorithms (GA) or a Particle Swarm Optimization (PSO) approach. Experiments on two different DMAs are used to evaluate the performance of the resolution methods as well as the efficiency achieved in the leak location when using the sensor placement results.
Optimal Sensor Placement for Leak Location in Water Distribution Networks Using Genetic Algorithms
Sensors, 2013
This paper proposes a new sensor placement approach for leak location in water distribution networks (WDNs). The sensor placement problem is formulated as an integer optimization problem. The optimization criterion consists in minimizing the number of non-isolable leaks according to the isolability criteria introduced. Because of the large size and non-linear integer nature of the resulting optimization problem, genetic algorithms (GAs) are used as the solution approach. The obtained results are compared with a semi-exhaustive search method with higher computational effort, proving that GA allows one to find near-optimal solutions with less computational load. Moreover, three ways of increasing the robustness of the GA-based sensor placement method have been proposed using a time horizon analysis, a distance-based scoring and considering different leaks sizes. A great advantage of the proposed methodology is that it does not depend on the isolation method chosen by the user, as long as it is based on leak sensitivity analysis. Experiments in two networks allow us to evaluate the performance of the proposed approach.
Sensor placement for leak detection and location in water distribution networks
Water Science & Technology: Water Supply, 2014
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 to a District Metered Area in the Barcelona Water Distribution Network.
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2014
The paper presents a method of water distribution system sensors placement. Location of sensors depends on the purpose of monitoring of a network. In this paper, this objective has been defined as the ability to detect network failures (leakages). Therefore, the location of monitoring points should be designed so as to maximize the effectiveness of the location method. The main objective of the algorithm deployment of sensors is to find a placement that minimizes the number of components for the largest collection of leakages (faults) with the same signature. The simplest way of determining the best sensors placement is to use an exhaustive search method. However, even a slight increase in the number of possible sensors locations makes exhaustive search very inefficient. Therefore, the selection of sensors placement was performed by optimization using evolutionary genetic algorithm. The computations were performed on the example of the water supply network in Glubczyce town in Polan...
Sensor Placement for Classifier-Based Leak Localization in Water Distribution Networks
Applied condition monitoring, 2017
This paper presents a sensor placement approach for classifier-based leak localization in water distribution networks. The proposed method is based on a hybrid feature selection algorithm that combines the use of a filter based on relevancy and redundancy with a wrapper based on genetic algorithms. This algorithm is applied to data generated by hydraulic simulation of the considered water distribution network and it determines the optimal location of a prespecified number of pressure sensors to be used by a leak localization method based on pressure models and classifiers proposed in previous works by the authors. The method is applied to a small-size simplified network (Hanoi) to better analyze its computational performance and to a mediumsize network (Limassol) to demonstrate its applicability to larger real-size networks.
Computers & Chemical Engineering
This paper presents a sensor placement approach for classier-based leak localization in water distribution networks. The proposed method is based on a hybrid feature selection algorithm that combines the use of a lter based on relevancy and redundancy with a wrapper based on genetic algorithms. This algorithm is applied to data generated by hydraulic simulation of the considered water distribution network and it determines the optimal location of a prespecied number of pressure sensors to be used by a leak localization method based on pressure models and classiers proposed in previous works by the authors. The method is applied to a small-size simplied network (Hanoi) to better analyze its computational performance and to a mediumsize network (Limassol) to demonstrate its applicability to larger real-size networks.
Optimal sensor placement for classifier-based leak localization in drinking water networks
2016
This paper presents a sensor placement method for classifier-based leak localization in Water Distribution Networks. The proposed approach consists in applying a Genetic Algorithm to decide the sensors to be used by a classifier (based on the k-Nearest Neighbor approach). The sensors are placed in an optimal way maximizing the accuracy of the leak localization. The results are illustrated by means of the application to the Hanoi District Metered Area and they are compared to the ones obtained by the Exhaustive Search Algorithm. A comparison with the results of a previous optimal sensor placement method is provided as well.
Water
Model-based and data-driven methods are commonly used in leak location strategies in water distribution networks. This paper formulates a hybrid methodology in two stages that complements the advantages and disadvantages of data-driven and model-based strategies. In the first stage, a support vector machine multiclass classifier is used to reduce the search space for the leak location task. In the second stage, leak location task is formulated as an inverse problem, and solved using a variation of the differential evolution algorithm called topological differential evolution. The robustness of the method is tested considering measurement and varying demand uncertainty conditions ranging from 5 to 15% of node nominal demands. The performance of the hybrid method is compared to the support vector machine classifier and topological differential evolution approaches as standalone methods of leak location. The hybrid proposal shows higher performance in terms of location accuracy, zone s...
Optimization Model and Algorithms for Design of Water Sensor Placement in Water Distribution Systems
Water Distribution Systems Analysis Symposium 2006, 2008
In this study we provide a methodology for the optimal design of water sensor placement in water distribution networks. The optimization algorithm used is based on a simulation-optimization and a single-objective function approach which incorporates multiple factors used in the design of the system. In this sense the proposed model mimics a multiobjective approach and yields the final design without explicitly specifying a preference among the multiple objectives of the problem. A reliability constraint concept is also introduced into the optimization model such that the minimum number of sensors and their optimal placement can be identified in order to satisfy a prespecified reliability criterion for the network. Progressive genetic algorithm approach is used for the solution of the model. The algorithm works on a subset of the complete set of junctions present in the system and the final solution is obtained through the evolution of subdomain sets. The proposed algorithm is applied to the two test networks to assess the selected design. The results of the proposed solution are discussed comparatively with the outcome of other solutions that were submitted to a water distribution systems analysis symposium. These comparisons indicate that the algorithm proposed here is an effective approach in solving this problem.
Water, 2015
In this paper, an original model-based scheme for leak location using pressure sensors in water distribution networks is introduced. The proposed approach is based on a new representation called the Leak Signature Space (LSS) that associates a specific signature to each leak location being minimally affected by leak magnitude. The LSS considers a linear model approximation of the relation between pressure residuals and leaks that is projected onto a selected hyperplane. This new approach allows to infer the location of a given leak by comparing the position of its signature with other leak signatures. Moreover, two ways of improving the method's robustness are proposed. First, by associating a domain of influence to each signature and second, through a time horizon analysis. The efficiency of the method is highlighted by means of a real network using several scenarios involving different number of sensors and considering the presence of noise in the measurements.