AN IMPROVED SYSTEM FOR ESTIMATING WATER FLOWS AT THE BOUNDARIES OF A SUB-NETWORK OF A WATER DISTRIBUTION NETWORK

    公开(公告)号:US20190310159A1

    公开(公告)日:2019-10-10

    申请号:US16315119

    申请日:2017-07-06

    申请人: SUEZ GROUPE

    IPC分类号: G01M3/28

    摘要: 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.

    METHOD FOR DETECTING ANOMALIES IN A DISTRIBUTION NETWORK, IN PARTICULAR A WATER DISTRIBUTION NETWORK

    公开(公告)号:US20170205267A1

    公开(公告)日:2017-07-20

    申请号:US15328515

    申请日:2015-07-23

    申请人: SUEZ GROUPE

    IPC分类号: G01F15/06 G01L19/08 G06F17/50

    摘要: 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.