Abstract
Digital image correlation (DIC) is a versatile non-contact optical measurement method, but it still has many shortcomings in theory and application. For example, the traditional DIC method has difficulty obtaining the desired result when the surface of the test object is rotated substantially or the deformation involves large rotation. Some scholars argue that a rotation angle greater than 7° will not work with the DIC algorithm, and this phenomenon is called decorrelation. To solve this problem, this study proposes the rotation-invariant DIC (RI-DIC) method that combines rotation-invariant template matching with traditional DIC. A pre-matching method based on ring projection transform (RPT) and orientation codes (OC) is proposed to provide the initial values for the DIC iteration process. The algorithm consists of three stages. In the first stage, the RPT process is used to convert the 2D template in a circular region into a 1D grey-level signal as a function of radius, and the template matching based on RPT is used to obtain a series of candidate points. The advantages of RPT process are the characterisation of its rotation invariance and the reduction of computational complexity. In the second stage, a fine matching process based on OC is performed on a limited number of candidate points to obtain the integer pixel matching position and the initial value. Finally, the inverse compositional Gauss–Newton (IC-GN) iteration method is used to further calculate the displacement and strain information accurately on the basis of the initial values. The novelty of this paper is to fuse the ring projection transform and orientation codes in machine vision into the traditional DIC algorithm, finally propose the RI-DIC algorithm. By the proposed method, we can measure the strain generated by the centrifugal force of a drone blade rotating at a high speed. Experimental results indicate that the method can accurately measure the surface deformation of a test object at any rotation angle.
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