  Pipelines for water supply are susceptible to burst-leakage due to fluid
pressures of various nature. High pressure heads resulting in circumferential
and (or) axial stresses larger than the material yield stress could cause pipe
failure. Of equal concern is the local boiling or cavitation effect in regions
of fluid pressure dropping below its vapor pressure, which in turn develop air
bubbles that get transported through the pipeline, bursting later at remote
locations. We initially developed a simple probabilistic model based on Method
of Characteristics (MOC) to simulate burst leakage in pipelines, and compared
with a pure deterministic hydraulic model. We had not considered cavitation
effects for simplicity. The results indicated that the simple probabilistic
model was only marginally different in its prediction of the transients on
comparison with the latter. In order to determine the position and amount of
leakage in the distribution system, the detection method based on simulating
hydraulic transients was further evaluated using Extended Kalman Filter (EKF).
We found that this non-linear filtering approach on the fluid transient model
considerably reduced the number of input parameters required, and it was able
to predict leakage rate and burst positions even in a highly noisy environment.

Signal Processing