A Vision-Based Sensor for Noncontact Structural Displacement Measurement

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.

A non-contact vision-based system for multipoint displacement monitoring in a cable-stayed footbridge

“…Efforts have been spent on developing advanced vision-based systems to provide accurate and robust displacement measurement primarily of high-rise buildings, [8] short-span bridges, [9][10][11][12] and long-span bridges. [10,[13][14][15][16] Previous studies have indicated the significant potential of vision-based systems for structural condition evaluation, especially for system identification.…”

“…• Correlation-based template matching is a classic and widely used technique, [8,9,13,14,16] which is realised by searching for an area in a new frame most closely resembling the reference (or template) that is predefined as a rectangular subset in the initial frame.…”

“…Correlation-based template matching has been applied for structural displacement monitoring on a railway bridge, [9] a long-span bridge, [16] and a high-rise building for tracking specific patterns, [13,14,44] light-emitting diode lamp targets, [16] and feature targets on structural surfaces. [9] One critical advantage of this method is the minimal user intervention, limited to specifying the template region in the reference frame. However, the method is sensitive to lighting changes [23,49] and changes of background conditions.…”

“…[53] The target location in the new frame corresponds to the peak location in the zero-mean normalised cross-correlation coefficient matrix that has the resolution at pixel level. Subpixel interpolation schemes [9] are required to refine the tracking results. The interpolation method used in this study is zero-padding in frequency domain using matrix multiplication form of discrete Fourier transform.…”

“…The analysis results are shown in Figures 19 and 20 for the cables C1 and C2, respectively. In [7,9] Hz with the estimated instantaneous frequencies marked as sparse dots terms of accelerometer measurement, instead of plotting directly the results near the fundamental frequency of the cable, higher frequency ranges, that is, near the fifth modal frequency for the measurement at A1 and near the third modal frequency for the measurement at A2, are illustrated in Figures 19b and 20b, with the corresponding values near the fundamental frequency marked in the right y axis. Figure 19a indicates the CWT analysis results for the measurement at the cable C1 by vision-based system.…”