Electromagnetic Tomography‐Based Detection of Defects in Carbon Fiber Reinforced Polymer Cables Using the Bound‐Constrained Split Bregman L1 Algorithm

ABSTRACT Electromagnetic tomography has emerged as a promising technique for defect detection in carbon fiber reinforced polymer (CFRP) cables, owing to its non‐contact and visual imaging capabilities. To address the challenges of the ill‐posedness and computational efficiency in defect imaging of CFRP cables, the Bound‐Constrained Split Bregman L1 method is proposed. The integration of L1 regularization with the Split Bregman solution method effectively mitigates the impact of measurement noise and enhances the spatial resolution of the reconstructed images. Defect reconstruction images of CFRP cables exhibit numerous artifacts due to their low electrical conductivity. Therefore, introducing a constrained lower bound consistent with physical conditions reduces imaging errors from edge artifacts. Numerical simulation results demonstrate that the proposed Bound‐Constrained Split Bregman L1 method outperforms conventional algorithms, including the Linear Back Projection, Landweber iterative, Tikhonov regularization, Iterative Shrinkage‐Thresholding algorithm, Alternating Direction Method of Multipliers, and Split Bregman L1 ‐regularized algorithms, and exhibits superior noise resistance and imaging stability. Specifically, the proposed Bound‐Constrained Split Bregman L1 method attained a mean Imaging Error (IE) of 0.182 and a Structural Similarity Index Measure (SSIM) of 0.948. This represents a 26%–60% decrease in IE and a 1.5%–6.6% increase in SSIM relative to all other methods evaluated. The method's superior defect detection in the experiment highlights its potential as a promising tool for electromagnetic tomography of CFRP cables.