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Proceedings Paper

Image-based dynamic deformation monitoring of civil engineering structures from long ranges
Author(s): Matthias Ehrhart; Werner Lienhart
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Paper Abstract

In this paper, we report on the vibration and displacement monitoring of civil engineering structures using a state of the art image assisted total station (IATS) and passive target markings. By utilizing the telescope camera of the total station, it is possible to capture video streams in real time with 10fps and an angular resolution of approximately 2″/px. Due to the high angular resolution resulting from the 30x optical magnification of the telescope, large distances to the object to be monitored are possible. The laser distance measurement unit integrated in the total station allows to precisely set the camera’s focus position and to relate the angular quantities gained from image processing to units of length. To accurately measure the vibrations and displacements of civil engineering structures, we use circular target markings rigidly attached to the object. The computation of the targets’ centers is performed by a least squares adjustment of an ellipse according to the Gauß-Helmert model from which the parameters of the ellipse and their standard deviations are derived. In laboratory experiments, we show that movements can be detected with an accuracy of better than 0.2mm for single frames and distances up to 30m. For static applications, where many video frames can be averaged, accuracies of better than 0.05mm are possible. In a field test on a life-size footbridge, we compare the vibrations measured by the IATS to reference values derived from accelerometer measurements.

Paper Details

Date Published: 27 February 2015
PDF: 14 pages
Proc. SPIE 9405, Image Processing: Machine Vision Applications VIII, 94050J (27 February 2015); doi: 10.1117/12.2075888
Show Author Affiliations
Matthias Ehrhart, Technische Univ. Graz (Austria)
Werner Lienhart, Technische Univ. Graz (Austria)


Published in SPIE Proceedings Vol. 9405:
Image Processing: Machine Vision Applications VIII
Edmund Y. Lam; Kurt S. Niel, Editor(s)

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