Report Open Access
The combined usage of the hydraulic model calibration residual and an improved vectorial angle method is presented for the burst detection and diagnosis in the L-Town network. It consists of five stages: (1) model decomposition, (2) partition of SCADA data, (3) nodal demand calibration, (4) calibration residual-based leakage detection, and (5) an improved vectorial angle method based burst localization. Compared with existing methods, the proposed method has the following advantages that make it a robust burst detection and localization approach. First, the bursts are detected based on the calibration residuals of nodal demands, by which the hydraulic model and SCADA data are taken into account simultaneously. Second, the concept of pipe sensitivity vectors is proposed, considering the burst occurs in the middle of pipelines. This sensitivity vector is calculated based on the nodes' sensitivity vectors at both ends of a pipe. It is then used to localize pipe detect the burst pipes accurately through calculating the angle between the calibration residual vector and each pipe sensitivity vector. The burst pipe is the sensitivity vector that presents the smallest angle with the residual vector. We first applied the method mentioned above to the pipe burst events reported in 2018. Then, our estimations regarding the location and start time of pipe bursts in 2019 are yield.