Abstract
The development of high-speed camera systems and image processing techniques has promoted the use of vision-based methods as a practical alternative for the analysis of non-contact structural dynamic responses. In this study, a deviation extraction method is introduced to obtain deviation signals from structural idealized edge profiles. Given that the deviation temporal variations can reflect the structural vibration characteristics, a method based on singular-value decomposition (SVD) is proposed to extract valuable vibration signals from the matrix composed of deviations from all video frames. However, this method exhibits limitations when handling low-level motions that reflect high-frequency vibration components. Hence, a video acceleration magnification algorithm is employed to enhance low-level deviation variations before the extraction. The enhancement of low-level deviation variations is validated by a light-weight cantilever beam experiment and a noise barrier field test. From the extracted waveforms and their spectrums from the original and magnified videos, subtle deviations of the selected straight-line edge profiles are magnified in the reconstructed videos, and low-level high-frequency vibration signals are successfully enhanced in the final extraction results. Vibration characteristics of the test beam and the noise barrier are then analyzed using signals obtained by the proposed method.
Highlights
The dynamic responses of structures with complex configurations, such as mechanical equipment, bridges, and buildings, are typically measured using a set of mounted transducers, such as accelerometers and strain gauges
This study proposes an approach for extracting the low-level valuable vibration signal from deviations of the structural idealized edge profile
Given that the relative intensity variations along the structural edge profile reflect their vibration characteristics, a method based on singular-value decomposition (SVD) is introduced to extract useful vibration signals involved in the analysis matrix
Summary
The dynamic responses of structures with complex configurations, such as mechanical equipment, bridges, and buildings, are typically measured using a set of mounted transducers, such as accelerometers and strain gauges. The variations in deviations are sensitive to structural low-frequency vibration, which has a relatively large amplitude This method exhibits limitations when handling low-level motions on the idealized edge profile that reflect high-frequency components. In this regard, the Eulerian video magnification (EVM) algorithm [27,28,29] is introduced to preprocess subtle high-frequency vibrations in video before deviation extraction. Only low-level small variations are magnified rather than large motions, such as object motion or the camera For this reason, an acceleration motion magnification is employed to handle high-speed video before deviation extraction [30]. The discussion and conclusions are presented in the final section
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