Burst identification of water distribution system using adaptive Kalman filter
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Abstract:
The pipe burst of water distribution systems (WDSs) can be alarmed on-line according to the abnormal change of measurements of Supervisory Control and Data Acquisition(SCADA) system. However, due to the periodic variation and random fluctuation of the water consumption, as well as the measurement errors, it is often hard to alarm the burst with small discharge in practice. To solve this problem, this paper proposes a method for burst alarming of WDSs based on adaptive Kalman filter, by which the historical data are first decomposed according to periodic variation of water consumption, and then the adaptive Kalman filter combined with the average low pass filter are used to estimate the water supply real-timely, finally the burst is alarmed and its discharge is estimated based on the difference between the measurements and the estimates. The test results from simulation data and real measurements indicate the proposed method is valid for burst alarming in practical application, and the accuracy of burst alarming is about 9% of the maximum hour water consumption. The accuracy of the burst alarming depends mainly on the random fluctuation of the water consumption itself, and is also related to the sampling frequency of measurements.
