Kalman Filtering of Hydraulic Measurements for Burst Detection in Water Distribution Systems
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 2, Issue 1
Abstract
Automatic burst and leak detection in water distribution systems plays an important role in water saving and management. This research develops a novel burst detection method of using adaptive Kalman filtering on hydraulic measurements of flow and pressure at district meter area (DMA) level. Adaptive Kalman filtering is used to model normal water usage (or alternatively water pressure), so the residual of the filter (e.g., the difference between the predicted flow and the measured flow) represents the amount of abnormal water usage relating to the bursts (or newly occurred leaks) in the downstream network. The results from a series of engineered tests which simulated flushing show that the size of the bursts and leaks strongly correlates with the residual of the filter. Finally, the method was applied to data from several real DMAs in the north of England, and the results show that the detected bursts correspond well to known historical operational information such as customer complaints’ records and work management (repair) data. The results suggest that flow measurement data are more sensitive to a burst or leak than the pressure measurement data.
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Acknowledgments
This work is part of the Neptune project funded by the U.K. Engineering and Physical Sciences Research Council, Grant No. EPSRCEP/E003192/1. The writers would like to thank Mr. Ridwan Patel (Yorkshire Water Services) and Professor Joby Boxall, Dr. John Machell, and Dr. Steve Mounce (University of Sheffield) for conducting fieldwork and assistance with data sets.
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Information
Published In
Journal of Pipeline Systems Engineering and Practice
Volume 2 • Issue 1 • February 2011
Pages: 14 - 22
Copyright
© 2011 ASCE.
History
Received: Feb 2, 2010
Accepted: Aug 24, 2010
Published online: Aug 31, 2010
Published in print: Feb 2011
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