Abstract
The development of image sensor and optics enables the application of vision-based techniques to the non-contact dynamic vibration analysis of large-scale structures. As an emerging technology, a vision-based approach allows for remote measuring and does not bring any additional mass to the measuring object compared with traditional contact measurements. In this study, a high-speed vision-based sensor system is developed to extract structure vibration signals in real time. A fast motion extraction algorithm is required for this system because the maximum sampling frequency of the charge-coupled device (CCD) sensor can reach up to 1000 Hz. Two efficient subpixel level motion extraction algorithms, namely the modified Taylor approximation refinement algorithm and the localization refinement algorithm, are integrated into the proposed vision sensor. Quantitative analysis shows that both of the two modified algorithms are at least five times faster than conventional upsampled cross-correlation approaches and achieve satisfactory error performance. The practicability of the developed sensor is evaluated by an experiment in a laboratory environment and a field test. Experimental results indicate that the developed high-speed vision-based sensor system can extract accurate dynamic structure vibration signals by tracking either artificial targets or natural features.
Highlights
Engineering structures including bridges and buildings are inevitably exposed to various external loads, such as traffic, earthquakes and gusts during their lifetime
The results indicate that the maximum cross-correlation (MCC)-based algorithm successfully extract the motion signals of the black circle in the simulation
Different from the upsampled cross-correlation (UCC) algorithm, which improves the fast Fourier transform (FFT) upsampling approach, the modified Taylor and the localization refinement algorithms provide more efficient alternatives in vision-based vibration measurements. Among these two proposed algorithms, the algorithm refined by rounding-iterative Taylor approximation can get more accurate results than the algorithm refined by subpixel localization and the algorithm refined by subpixel localization is more efficient than the algorithm refined by rounding-iterative Taylor approximation
Summary
Engineering structures including bridges and buildings are inevitably exposed to various external loads, such as traffic, earthquakes and gusts during their lifetime. These external loads may induce structure damage and lead to life-threatening materials’ failure. Conventional sensors like accelerometers [1] are widely employed in monitoring system to obtain valuable vibration information for mechanical analysis or structure safety evaluation. Conventional sensors can only obtain vibration acceleration signal, which does not provide an intuitionistic exhibition of the actual vibration. Most of the non-contact equipment require high costs and are composed of complex structures; these systems can hardly be used widely in practical applications
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