Improving Dam Deformation Analysis Using Least-Squares Variance Component Estimation and Tikhonov Regularization
Publication: Journal of Surveying Engineering
Volume 147, Issue 1
Abstract
Several least-squares adjustment techniques were tested for dam deformation analysis. Deformation monitoring had only been studied horizontally. Simulated observations were first performed to compare the three methods of least-squares: observations with their initial weight, observations with the estimated variance component, and the regularization method. The best scenario was adopted for the real network. The results demonstrated that a more accurate outcome is possible by least-square variance component estimation (LS-VCE). Comparison of the estimated and simulated displacements in the LS-VCE method indicated that the difference for the two east–west and north–south components is 0.05 and 0.08 mm, while this difference in the other two modes is 1.02 and 0.67 mm for observations with their initial weight, and 0.64 and 0.16 mm for the Tikhonov regularization method, respectively. In the best method, an improvement was found in the standard deviation of the east–west, south–north components, the estimation of the major axis of the error ellipse, and the trace of the variance–covariance matrix of unknowns, in comparison with the other methods.
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Data Availability Statement
Some or all data, models, or code used during the study were provided by a third party. Direct requests for these materials may be made to the provider as indicated in the Acknowledgments.
Acknowledgments
The authors would like to thank the anonymous reviewers for their constructive comments on an earlier version of this article. The useful comments of the editor David Protas and an anonymous reviewer are gratefully acknowledged. The authors acknowledge the use of Jamishan Dam data that are freely provided by Tarh and Naghshe Bakhtar Consulting Engineering Company.
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© 2020 American Society of Civil Engineers.
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Received: Dec 19, 2019
Accepted: Aug 4, 2020
Published online: Nov 3, 2020
Published in print: Feb 1, 2021
Discussion open until: Apr 3, 2021
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