To address the requirements for defect detection and three-dimensional (3D) visualization requirements of defects in carbon fiber composite cables (CFCC), a 3D reconstruction method integrating cross-sectional and surface electromagnetic tomography is proposed. First, the cross-sectional and surface sensitivity matrices of the CFCC are constructed. By combining algebraic reconstruction techniques with singular value decomposition for dimensionality reduction, two-dimensional (2D) imaging of typical defect modes is reconstructed for both cross-sectional and surface views. On this basis, a priori knowledge of the regular geometry of CFCC and a triple-constraint verification mechanism are introduced to achieve the fusion and inversion of 2D information into 3D defect morphology. It is shown that cross-sectional imaging exhibits relatively superior performance in the correlation coefficient metric (0.516–0.679), facilitating defect localization, whereas surface imaging demonstrates greater prominence in the structural similarity metric (0.949–0.979) for better preservation of defect contours. The proposed 3D reconstruction method enables visualization of defect spatial distribution and effectively eliminates interference from non-defect information through a constrained verification mechanism. Therefore, it overcomes the limitations of single-view imaging. This imaging method provides a viable solution for the rapid detection and 3D visualization of CFCC defects.
Wáng et al. (Tue,) studied this question.