Damage detection is important for sensing and analyzing the degradation of structures, and can effectively avoid potential catastrophic failures. Among the numerous studies in literature, most emphasis was given to the damage detection based on vibration response signals for simple beam structures. In this paper, the feasibility of roughness method for plates was investigated using both vibration-based data and static deformation data. Two detection methods, namely, roughness method and fractal dimension method, were used to analyze the data. Both types of data were obtained for aluminum plates using finite element simulation. It was found that both methods were able to detect the damage and locate its position precisely with the two types of signals. The effectiveness of damage detection using static deformation data was further demonstrated by experimenting with a cracked cantilever beam. A computer vision camera efficiently and automatically collected the static deformation data, and this approach showed great potential compared with the expensive and time-consuming collection process for vibration response data such as mode shapes.

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