Defect Detection of Carbon Fiber Cables by Electromagnetic Tomography Based on Proximal Gradient Method

Carbon fiber-reinforced polymer (CFRP) cables have been widely applied in modern engineering due to their excellent mechanical properties and durability, and their service safety has received increasing attention. However, there is currently a lack of efficient and accurate methods for detecting defects in CFRP cables. This article proposes a CFRP cable defect detection method based on electromagnetic tomography (EMT) technology to provide technical support for ensuring the safe service of cables. Due to the ill-posedness and instability of the inverse problem of EMT, there are reconstruction errors in the image reconstruction results. To address the EMT image reconstruction problem, an L1 regularization image reconstruction algorithm based on the proximal gradient method is proposed, which improves the defect reconstruction ability and reconstruction accuracy of the algorithm. First, the objective function is gradually optimized by combining gradient descent and proximal mapping operations to achieve variable-step-size gradient descent to handle the solution problems caused by the nonsmooth terms of the regularization function. On this basis, the image color mapping is adjusted to suppress the artifacts and noise in the reconstructed image. Finally, the proposed method is verified by carbon fiber composite material cables with different defect distributions. The numerical and experimental results show that the proposed method has stronger defect detection ability and can obtain high-quality defect reconstruction results. Compared with traditional methods, the image evaluation indicators have increased by 29.6% and 51.7%, respectively.