Experimental Observation and Analysis of Inverse Transients for Pipeline Leak Detection
Publication: Journal of Water Resources Planning and Management
Volume 133, Issue 6
Abstract
Fluid transients result in a substantial amount of data as pressure waves propagate throughout pipes. A new generation of leak detection and pipe roughness calibration techniques has arisen to exploit those data. Using the interactions of transient waves with leaks, the detection, location, and quantification of leakage using a combination of transient analysis and inverse mathematics is possible using inverse transient analysis (ITA). This paper presents further development of ITA and experimental observations for leak detection in a laboratory pipeline. The effects of data and model error on ITA results have been explored including strategies to minimize their effects using model error compensation techniques and ITA implementation approaches. The shape of the transient is important for successful application of ITA. A rapid input transient (which may be of small magnitude) contains maximum system response information, thus improving the uniqueness and quality of the ITA solution. The effect of using head measurements as boundary conditions for ITA has been shown to significantly reduce sensitivity, making both detection and quantification problematic. Model parsimony is used to limit the number of unknown leak candidates in ITA, thus reducing the minimization problem complexity. Experimental observations in a laboratory pipeline confirm the analysis and illustrate successful detection and quantification of both single and multiple leaks.
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Acknowledgments
The writers thank the Australian Research Council for financial support. The first writer is grateful to the Australian Government for a scholarship during the time he was a doctoral candidate.
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Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 133 • Issue 6 • November 2007
Pages: 519 - 530
Copyright
© 2007 ASCE.
History
Received: Aug 9, 2005
Accepted: Nov 16, 2005
Published online: Nov 1, 2007
Published in print: Nov 2007
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