Carbon fiber composites have excellent properties such as high specific strength, high specific stiffness, corrosion resistance and fatigue resistance, which are ideal construction materials for large-span structural cables. In this paper, a simulation study of broken strands and debonding in carbon fiber cables was carried out using the finite element method based on the electromagnetic tomography technique, and an 8-coil circumferential sensor array was designed to investigate the relationship between the sensor dimension, the magnitude of the excitation current and the magnetic induction intensity. The effects of three reconstruction algorithms, LBP algorithm, Tikhonov algorithm and Landweber algorithm, on the quality of reconstructed images of different cables defects were investigated based on the simulated electromagnetic signals. The results show that as the diameter of the sensor coils decreases and the excitation current increases within the studied range, the magnetic field intensity progressively increases. When the diameter of the sensor coils is 5 mm and the excitation current is 1 A, the magnetic field intensity reaches its maximum value.Compared with other image reconstruction methods, the Tikhonov is suitable for the reconstruction process of defect detection images in carbon fiber cables due to Tikhonov algorithm can better balance the image reconstruction effect and imaging quality. In addition, the effect of different projection angles on defect imaging was analyzed by rotating the cable defect with a fixed sensor array. The study aims to provide a reference basis for the design of sensor arrays and defect detection imaging of carbon fiber cables under experimental conditions.