To recover the identification code information of damaged characters of mechanical equipment, this paper proposes a magneto-optical imaging restoration method for damaged characters with orthogonal excitation. Based on the study of the influence mechanism of steel matrix characters on magnetic field conduction, a ring electromagnet model with time-sharing orthogonal excitation is developed, and the effectiveness of the model is verified through simulation analysis. First, to enhance the magneto-optical images of characters obtained by orthogonal excitation, we employ the local histogram equalization method to highlight the stroke features of characters. Then, we design the fusion algorithm of pixel-level significant value weighted average to fuse the images. The experimental system was designed to obtain magneto-optical images with orthogonal directional excitation, and the effectiveness of the proposed algorithm was evaluated through experiments. The results show that the magneto-optical images enhanced by local histogram equalization have large contrast of character strokes and high resolution, verifying the effectiveness of the proposed algorithm. Furthermore, the pixel-level salient value weighted fusion algorithm can comprehensively and efficiently extract all directional features of the character images when fusing the magneto-optical images of damaged characters, and the fused images have high definition. Therefore, the proposed magneto-optical imaging restoration method for damaged characters with orthogonal excitation can effectively recover severely damaged characters with complex strokes.