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Sparse-view CT reconstruction method for in-situ non-destructive testing of reinforced concrete

NONDESTRUCTIVE TESTING AND EVALUATION(2023)

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Abstract
X-ray CT is an important in-situ non-destructive testing method that plays an important role in both production and materials research. In-situ CT of concrete can acquire images of concrete slices in the state of holding force loading, which is meaningful for the study of concrete crack development characteristics. However, existing X-ray CT equipment either cannot penetrate large reinforced concrete due to energy limitations or does not address the extremely sparse angular reconstruction problem associated with in-situ testing. In this paper, a sinogram Transformer method based on a priori projection data is proposed to solve this extremely sparse data complementation problem on a large-scale electron accelerator X-ray in-situ CT system. The simulated concrete sparse-view projection data and the full projection data are used as the input and label of the proposed method in order to experiment the method. The results demonstrate the feasibility of using a priori projected sine diagrams with ultra-sparse sine diagram residuals to track sine diagram variation, and verify that structures such as cracks and reinforcement, which dominate the deformation residuals of sinograms in concrete sections, can also be successfully recovered using Transformer in the ultra-sparse view projection of views 4-8.
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Key words
In-situ non-destructive testing,sparse-view CT,concrete testing,deep learning
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