Filtering Bad Measurement Data for Water Distribution System Demand Estimation
Publication: Journal of Water Resources Planning and Management
Volume 136, Issue 4
Abstract
Demand estimation has been solved by using a weighted least-squares (WLS) estimator incorporating field measurements with system simulation model. WLS estimator results are sensitive to spurious measurements caused by supervisory control and data acquisition malfunctions. Estimates using the contaminated measurements are not reliable and bad data should be filtered prior to demand estimation. This study presents a series of statistical methods to detect bad data, identify their locations, and correct the data values. The proposed methods are based on a linear measurement model that linearly relates state variables (nodal demands) to the field measurements (pipe flow rates). Application to a simple hypothetical network using synthetically generated data shows that the method can be successfully used as a preprocessing for single and multiple noninteracting bad data for reliable demand estimation.
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Acknowledgments
This work was supported by the University of Arizona, Technology and Research Initiative Fund (TRIF), Water Sustainability Program.
References
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Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 136 • Issue 4 • July 2010
Pages: 512 - 517
Copyright
© 2010 ASCE.
History
Received: Apr 1, 2009
Accepted: Sep 11, 2009
Published online: Oct 2, 2009
Published in print: Jul 2010
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