Abstract: A system for measuring water flows in a sub-network of a water distribution network is provided. The system includes a plurality of sensors, for example pressure sensors, on the network. The system further comprises communication links between the sensor and one a computing device, and a measurement acquisition system. The computing device is configured to retrieve values of measurements, directly or through the measurement acquisition system; use values of measurements to determine values of control variables of a model of the water distribution network which minimize residue values between measurements values and predicted physical values on the network; then use the model parameter with the values of control variables to calculate water flows at the boundaries of the sub-network.

Abstract: A method and a system for detecting anomalies in a water distribution system comprises a network of nodes, and is equipped with sensors of at least water velocity at a subset of the nodes. The water distribution system is modeled by a hydraulic model. The method comprises parametrizing the hydraulic model with initial values of a set of control variables, using the sensors to obtain values of state variables of the network at the nodes, using the hydraulic model to calculate predicted values of state variables, recursively calculating the values of control variables which, applied to the hydraulic model, permit to obtain the predicted values of state variables the closest to the observed values, and classifying nodes of the network based on the values of control variables.

Abstract: A system for measuring water flows in a sub-network of a water distribution network is provided. The system includes a plurality of sensors, for example pressure sensors, on the network. The system further comprises communication links between the sensor and one a computing device, and a measurement acquisition system. The computing device is configured to retrieve values of measurements, directly or through the measurement acquisition system; use values of measurements to determine values of control variables of a model of the water distribution network which minimize residue values between measurements values and predicted physical values on the network; then use the model parameter with the values of control variables to calculate water flows at the boundaries of the sub-network.

Abstract: A method for the detection of anomalies in a networked water distribution system is provided. It improves detection methods based on an iterative modification of control variables of the network, by determining a reduced set of entities of the water distribution network on which control variables should be iteratively modifier. The invention increases the computing costs, and the reliability of such methods of detecting anomalies in a water distribution system.

Abstract: A hydraulic model of the network is used that describes the structural data and the laws governing the distributed flows. The model is fed with operational data relative to primary input parameters and, using the model, theoretical values are obtained for primary output parameters. The theoretical values are compared with measured values. In case of a significant deviation, the corresponding primary output parameter becomes a secondary input parameter in an inverse model including new secondary output parameters, which are added relative to the direct model and which correspond to primary input parameters. The secondary output parameters are, by priority, those to which the primary output parameter exhibiting the abnormal value is particularly sensitive. If necessary, the method is implemented iteratively by progressively restricting the number of the secondary output parameters.

Abstract: A method and a system for detecting anomalies in a water distribution system comprises a network of nodes, and is equipped with sensors of at least water velocity at a subset of the nodes. The water distribution system is modeled by a hydraulic model. The method comprises parametrizing the hydraulic model with initial values of a set of control variables, using the sensors to obtain values of state variables of the network at the nodes, using the hydraulic model to calculate predicted values of state variables, recursively calculating the values of control variables which, applied to the hydraulic model, permit to obtain the predicted values of state variables the closest to the observed values, and classifying nodes of the network based on the values of control variables.

Abstract: A hydraulic model of the network is used that describes the structural data and the laws governing the distributed flows. The model is fed with operational data relative to primary input parameters and, using the model, theoretical values are obtained for primary output parameters. The theoretical values are compared with measured values. In case of a significant deviation, the corresponding primary output parameter becomes a secondary input parameter in an inverse model including new secondary output parameters, which are added relative to the direct model and which correspond to primary input parameters. The secondary output parameters are, by priority, those to which the primary output parameter exhibiting the abnormal value is particularly sensitive. If necessary, the method is implemented iteratively by progressively restricting the number of the secondary output parameters.