The final thesis presents a crack identification method based on the digital image correlation technique. The methodology included synthetic testing of optical methods, followed by a real experiment in which we excited aluminum samples by a shaker and observed the high-frequency crack opening with a fast camera. The image analysis was performed in the Python software environment. In all the three samples, cracks were identified at an early stage.
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