A Eulerian Video Magnification Based Structural Damage Identification Method for Scaffold

Scaffolds are temporary structure with many safety hazards in the construction site. Vibration information of scaffold can reflect its health state. Traditional vibration measurement methods are measured by contact sensors, which have the disadvantages of complicated operation, high cost and low efficiency. This paper proposes a structural damage identification method for scaffold based on phased-based Eulerian video magnification algorithm. The digital image of scaffold vibration collected by digital camera is firstly processed by phased-based Eulerian video magnification to acquire motion-magnified image sequence in the particular frequency bands. Then, canny edge detector is used to identify the edges in the image sequence and eliminate the noise resulted from the magnification. The edges in the image sequence are utilized to acquire time-history data of scaffold displacement based on the geometry centroid, from which we can obtain resonant frequencies after Fourier transformation and finally identify the damage states. The applicability of the proposed method is discussed in the context of the frame scaffold experiments with 10 kinds of damage states. By comparing the results between camera measurement and accelerometer measurement, the proposed method has satisfactory performance with average error of 0.95%.