Abstract:
SUMMARY
Structural health monitoring is an emergent powerful diagnostic tool that can be used to identify and to
prevent possible failures of the various components that comprise an infrastructure. In a suspension
bridge,
the measurement of the vertical and transversal displacements plays an important role for its safety
evaluation. Considering the restrictions usually found on these structures, an enhanced solution comprises
a non-contact vision-based measurement system with dynamic response, accuracy and amplitude range
well suited to the physical phenomenon to measure.
A methodology to perform the vision system calibration is described, which can be carried out in situ,
while the deck is moving, requiring little effort and a minimum set of information. The key idea is to use
the factorization method to get an initial estimation of the object shape and camera’s parameters, and to
incorporate the knowledge about the distances between the calibration targets in a non-linear optimization
process to achieve a metric shape reconstruction and optimize the camera’s parameters estimation.
Results obtained by numerical simulation experiments are reported, showing the negligible influence of
noisy calibration data in the calibration performance and also the robustness of the calibration process on
the camera’s parameters estimation. Tests carried out to assess the calibration and tracking of the bridge
deck motion showed that, even in an environmental severely affected by noise, it is possible to measure
the vertical and transversal displacements of the bridge deck with excellent levels of accuracy.
