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Sensors 2018, 18(3), 756;

Estimating and Comparing Dam Deformation Using Classical and GNSS Techniques

Politecnico di Milano, Department of Civil and Environmental Engineering (DICA)—Geomatics and Geodesy Section, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
Author to whom correspondence should be addressed.
Received: 22 January 2018 / Revised: 20 February 2018 / Accepted: 23 February 2018 / Published: 2 March 2018
(This article belongs to the Special Issue Sensors for Deformation Monitoring of Large Civil Infrastructures)
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Global Navigation Satellite Systems (GNSS) receivers are nowadays commonly used in monitoring applications, e.g., in estimating crustal and infrastructure displacements. This is basically due to the recent improvements in GNSS instruments and methodologies that allow high-precision positioning, 24 h availability and semiautomatic data processing. In this paper, GNSS-estimated displacements on a dam structure have been analyzed and compared with pendulum data. This study has been carried out for the Eleonora D’Arborea (Cantoniera) dam, which is in Sardinia. Time series of pendulum and GNSS over a time span of 2.5 years have been aligned so as to be comparable. Analytical models fitting these time series have been estimated and compared. Those models were able to properly fit pendulum data and GNSS data, with standard deviation of residuals smaller than one millimeter. These encouraging results led to the conclusion that GNSS technique can be profitably applied to dam monitoring allowing a denser description, both in space and time, of the dam displacements than the one based on pendulum observations. View Full-Text
Keywords: dam; monitoring; GNSS; predictive modeling; collimators; pendulum; displacement detection; time series dam; monitoring; GNSS; predictive modeling; collimators; pendulum; displacement detection; time series

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Barzaghi, R.; Cazzaniga, N.E.; De Gaetani, C.I.; Pinto, L.; Tornatore, V. Estimating and Comparing Dam Deformation Using Classical and GNSS Techniques. Sensors 2018, 18, 756.

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