Leaks are present to some extent in all water-distribution systems. This paper proposes a leakage localisation method based on the pressure measurements and pressure sensitivity analysis of nodes in a network. The sensitivity analysis using analytical tools is not a trivial job in a real network because the huge non-explicit non-linear systems of equations that describe its dynamics. Simulations of the network in presence and absence of leakage may provide an approximation of this sensitivity. This matrix is binarised using a threshold independent of the node. The binary matrix is assumed as a signature matrix for leakages. However, there is a trade-off between the resolution of the leakage isolation procedure and the number of available pressure sensors. In order to maximise the isolability with a reasonable number of sensors, an optimal sensor placement methodology, based on genetic algorithms, is also proposed. These methodologies have been developed for Barcelona Network using PICCOLO simulator. The sensor placement and the leakage detection and localization methodologies are applied to several district management areas (DMA) in simulation and in reality.

This paper deals with the use of optimal control techniques in water distribution networks. An optimal control tool, developed in the context of a European research project is described and the application to the city of Sintra (Portugal) is presented.

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The trajectory control problem, defined as making a vehicle follow a pre-established path in space, can be solved by means of trajectory tracking or path following. In the trajectory tracking problem a timed reference position is tracked. The path following approach removes any time dependence of the problem, resulting in many advantages on the control performance and design. An exhaustive review of path following algorithms applied to quadrotor vehicles has been carried out, the most relevant are studied in this paper. Then, four of these algorithms have been implemented and compared in a quadrotor simulation platform: Backstepping and Feedback Linearisation control-oriented algorithms and NLGL and Carrot-Chasing geometric algorithms.

This paper proposes a leakage detection method based on detecting significant discrepancies between pressure measurements and their estimations obtained from the simulation of a calibrated water distribution network model. Every sensor in the network will allow to detect a discrepancy in pressure due to leakage depending on its location. Then, a set of well distributed pressure sensors will generate a leakage signature that allows leakage localisation. This paper presents the methodology used in the Barcelona network for distributing properly the sensors for a good discrimination in the leakage localisation process. The methodology for sensor placement uses the pressure sensitivity matrix to the leakage presence. This matrix is normalised and binarised in order to be used as a leakage signature matrix using the standard model based fault diagnosis approach. Sensors may be installed in any node and leakages are simulated as a constant demand that can appear in any node too. The problem of deciding which are the best localisations for a small number of sensors in order to detect and localise leakages is an inverse problem that should be solved using optimisation. The resulting optimisation problem is of discrete nature and very huge for a real network. This type of problem is, in general, hard to solve and very time consuming. The use of GA (Genetic Algorithms) has been proved adequate according to the formulation of the signatures in the sensitivity matrix.

The success in the application of any model-based methodology (e.g. design, control, supervision) highly depends on the availability of a well calibrated model. The calibration in water distribution networks needs to be performed online due to the continuous evolution of demands. During the calibration process, background leakages or bursts can be unintentionally incorporated to the demand model and treated as a system evolution (change in demands). This work proposes a leak detection and localization approach to be coupled with a calibration methodology that identifies geographically distributed parameters. The approach proposed consists in comparing the calibrated parameters with their historical values to assess if changes in these parameters are caused by a system evolution or by the effect of leakage. The geographical distribution allows to associate an unexpected behavior of the calibrated parameters (e.g. abrupt changes, trends, etc.) to a specific zone in the network. The performance of the methodology proposed is tested on a real water distribution network using synthetic data. Tested scenarios include leaks occurring at different locations and ranging from 2.5% to 13% of the total consumption. Leakage is represented as pressure-dependent demand simulated as emitter flows at the network nodes. Results show that even considering a low number of sensors, leaks with an effect on parameters higher than the parameters' uncertainty can be correctly detected and located within 200 meters.

Abstract:This paper describes a model-driven decision-support system (software tool) implementing a model-based methodology for on-line leakage detection and localization which is useful for a large class of water distribution networks. Since these methods present a certain degree of complexity which limits their use to experts, the proposed software tool focuses on the integration of a method emphasizing its use by water network managers as a decision support system. The proposed software tool integrates a model-based leakage localization methodology based on the use of on-line telemetry information, as well as a water network calibrated hydraulic model. The application of the resulting decision support software tool in a district metered area (DMA) of the Barcelona distribution network is provided and discussed. The obtained results show that the leakage detection and localization may be performed efficiently reducing the required time.