A sliding window method to identify defects in 3D printing lattice structure based on the difference principle

Abstract Structural defects are inevitably produced by residual stress in the 3D printing process, which reduce the structural-functional properties. For a typical 3D printing lattice structure, a new sliding window approach to intelligently identify defects, based on the difference principle, in the inspection process was proposed. Industrial computed tomography (CT) was used for image information acquisition. The grayscale standard deviation in the local range of the CT slice is calculated to characterize the grayscale variation of the defect location. On this basis, a sliding window method is proposed for traversing CT slices. Three different sizes of window and the corresponding calculation methods were established, and then the appropriate window was selected through comparison. After differential processing is performed on the traversed image to extract the defect feature, automatic defect recognition rules are created. The experimental results show that the recognition rate of the proposed method is 98.5% for typical internal defects of metal 3D lattice structures and the validity of the method is verified. Compared with a manual marking method, this method can effectively improve the efficiency of defect detection.