Abstract
In our study, a deviation extraction method is introduced to obtain subtle deviation signals from structural idealized edge profiles. The deviations are employed to reconstruct an analysis matrix that consists of global translations along selected edge profiles, and then a singular value decomposition-based approach is proposed to extract valuable variations from the calculated analysis matrix. To avoid noises from textured edge profiles, a colorization optimization approach is applied to remove variations because of the textures and turn real image stripes into ones that satisfy the constant edge profile assumption more closely in the deviation extraction process. Two practical experiments are conducted to demonstrate the effectiveness and potential applications of our proposed method. The dynamic properties of a lightweight beam and a sound barrier are analyzed successfully by using high-speed videos.
Highlights
With the development of camera systems and image processing techniques in recent years, vision-based approaches have been implemented as one of the most popular noncontact measurement approaches in areas such as structural health monitoring[1,2,3] and nondestructive testing.[4,5,6] Different from traditional contact accelerometers and strain gauges, these burgeoning noncontact alternatives are far more convenient for installation in conditions wherein contact sensors have difficult access and intuitive exhibition of the measurement target are provided
This study proposes an approach capable of extracting valuable information from intensity variations along structural edge profiles by using a singular value decomposition (SVD)-based method
SVD decomposition results indicated that signals corresponding to the first three singular values occupy over 95% of energy in the analysis matrix
Summary
With the development of camera systems and image processing techniques in recent years, vision-based approaches have been implemented as one of the most popular noncontact measurement approaches in areas such as structural health monitoring[1,2,3] and nondestructive testing.[4,5,6] Different from traditional contact accelerometers and strain gauges, these burgeoning noncontact alternatives are far more convenient for installation in conditions wherein contact sensors have difficult access and intuitive exhibition of the measurement target are provided. Intensity-based motion estimation methods, such as Horn–Schunck[25] and Lucas–Kanade optical flows,[12] calculate the relative spatial and temporal derivative fields by solving the aperture equation at each pixel between consecutive frames As these techniques theoretically are sensitive to image noise and disturbances, phase information[26,27] is adopted instead of raw pixel intensity values of images to enhance the robustness of intensity-based algorithms when facing illumination variations and noise conditions. This study proposes an approach capable of extracting valuable information from intensity variations along structural edge profiles by using a singular value decomposition (SVD)-based method. As the relative intensity variations along structural edge profiles contain their vibration characteristics, SVD is applied to extract useful vibration signals involved in the analysis matrix. The proposed method and high-speed camera systems thoroughly examine the dynamic responses of a clamped cantilever beam and a sound barrier
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