Abstract
Conventional displacement sensors have limitations in practical applications. This paper develops a vision sensor system for remote measurement of structural displacements. An advanced template matching algorithm, referred to as the upsampled cross correlation, is adopted and further developed into a software package for real-time displacement extraction from video images. By simply adjusting the upsampling factor, better subpixel resolution can be easily achieved to improve the measurement accuracy. The performance of the vision sensor is first evaluated through a laboratory shaking table test of a frame structure, in which the displacements at all the floors are measured by using one camera to track either high-contrast artificial targets or low-contrast natural targets on the structural surface such as bolts and nuts. Satisfactory agreements are observed between the displacements measured by the single camera and those measured by high-performance laser displacement sensors. Then field tests are carried out on a railway bridge and a pedestrian bridge, through which the accuracy of the vision sensor in both time and frequency domains is further confirmed in realistic field environments. Significant advantages of the noncontact vision sensor include its low cost, ease of operation, and flexibility to extract structural displacement at any point from a single measurement.
Highlights
Civil engineering structures including buildings and bridges are exposed to various external loads such as traffic, gust and earthquake during the operational lifetime
It is noted that the camera optical axis is tilted by an approximate angle of 15° with respect to the normal direction of the bridge surface, in this field test, due to the large height between ground and the bridge bottom surface, it is very difficult to install a reference LVDT to compare the accuracy of the measured displacement time histories by the vision sensor
A vision sensor system is developed for remote measurement of structural displacements based on an advanced subpixel template matching technique, namely, the upsampled cross correlation by means of Fourier transform
Summary
Civil engineering structures including buildings and bridges are exposed to various external loads such as traffic, gust and earthquake during the operational lifetime. It requires reflecting surfaces mounted on the structure [5] To cope with these problems, noncontact vision-based displacement measurement systems have been developed recently, which are primarily enabled by the template matching/registration techniques [1,2,3,9,10,11,12,13,14,15,16,17,18,19]. On the basis of a robust orientation code matching (OCM) algorithm, the authors developed a vision sensor system for real-time displacement measurement by tracking natural targets on the structural surface, which eliminates the requirement for physical access to structures to install artificial target panels [2,20]. The paper is organized as follows: in Section 2, the estimation of scaling factor is discussed, and the vision sensor system including the hardware and the theoretical background of the software is introduced; Section 3 evaluates its performance through a laboratory shaking table test of a small-scale frame structure; Section 4 presents two field tests results of a railway bridge and a pedestrian bridge, respectively; Section 5 concludes this study
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