Dynamic testing of a laboratory model via vision-based sensing

In the class of not-contact sensors, the techniques of vision-based displacement estimation enable one to
gather dense global measurements of static deformation as well as of dynamic response. They are becoming
more and more available thanks to the ongoing technology developments. In this work, a vision system,
which takes advantage of fast-developing digital image processing and computer vision
technologies and provides high sample rate, is implemented to monitor the 2D plane vibrations of a
reduced scale frame mounted on a shaking table as available in a laboratory. The physical meanings of
the camera parameters, the trade-off between the system resolution and the field-of-view, and the upper
limitation of marker density are discussed. The scale factor approach, which is widely used to convert the
image coordinates measured by a vision system in the unit of pixels into space coordinates, causes a poor
repeatability of the experiment, an unstable experiment precision, and therefore a global poor flexibility.
To overcome these problems, two calibrations approaches are introduced: registration and direct linear
transformation. Based on the constructed vision-based displacement measurement system, several
experiments are carried out to monitor the motion of a scale-reduced model on which dense markers
are glued. The experiment results show that the proposed system can capture and successfully measure
the motion of the laboratory model within the required frequency band.