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: Disclosed is a device for measuring at least one physical, chemical or biological parameter of a fluid, flowing in a pipe belonging to a fluid-distribution network, the device being installed in a cut on the pipe at the fluid delivery point, the pipe thus including a first section and a second section, the device including at least one sensor provided with a measurement end. The device also includes: a body including an opening forming a flow line, and at least one insertion recess capable of receiving the measurement end of the at least one sensor, the insertion recess opening into the flow line; an attachment unit arranged to connect a first end of the flow line with an end of the first section and a second end of the flow line with an end of the second section, to allow the fluid to flow through the flow line.

Abstract: Disclosed is a method for detecting anomalies in a distribution network equipped with sensors. The steps are: acquiring for each sensor a time series of physical measurements separated by time intervals; defining time windows each corresponding to a plurality of successive time intervals; extracting operational characteristics of each time series in each time window; forming, for each time window, at least one current vector having for coordinates the operational characteristics, structural data relating to the network and situational characteristics specific to the time window; comparing the current vector with preceding vectors corresponding to preceding time windows and the situational characteristics and structural data of which are similar to those of the current vector; and signalling an anomaly in cases where the current vector is significantly dissimilar to the preceding vectors.

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: Disclosed is a device for measuring at least one physical, chemical or biological parameter of a fluid, flowing in a pipe belonging to a fluid-distribution network, the device being installed in a cut on the pipe at the fluid delivery point, the pipe thus including a first section and a second section, the device including at least one sensor provided with a measurement end. The device also includes: a body including an opening forming a flow line, and at least one insertion recess capable of receiving the measurement end of the at least one sensor, the insertion recess opening into the flow line; an attachment unit arranged to connect a first end of the flow line with an end of the first section and a second end of the flow line with an end of the second section, to allow the fluid to flow through the flow line.

Abstract: Disclosed is a method for detecting anomalies in a distribution network equipped with sensors. The steps are: acquiring for each sensor a time series of physical measurements separated by time intervals; defining time windows each corresponding to a plurality of successive time intervals; extracting operational characteristics of each time series in each time window; forming, for each time window, at least one current vector having for coordinates the operational characteristics, structural data relating to the network and situational characteristics specific to the time window; comparing the current vector with preceding vectors corresponding to preceding time windows and the situational characteristics and structural data of which are similar to those of the current vector; and signalling an anomaly in cases where the current vector is significantly dissimilar to the preceding vectors.

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.