This paper proposes an approach for analyzing the microstructure evolution of laser welding seam by magneto-optical imaging (MOI). The Faraday magneto-optical effect and magnetic domain theory are used to account for the MOI mechanism. The influence of laser welding on the welded joint was inspected by the analysis of color, grayscale and brightness of magneto-optical images. The relation between the brightness of magneto-optical image and grain size of microstructure is discussed as well, and the characteristics of magneto-optical images of weld microstructure were compared with those of scanning electron microscope (SEM) images. Experimental results show that three regions, including the weld zone (WZ), the heat-affected zone (HAZ), and the base metal (BM) are distributed in the magneto-optical image of the welded joint. The MOI method can investigate the microstructure evolution of welded joints and provide a theory and experimental basis for detecting weld defects.

Using the traditional magneto-optical detection methods, micro-weld defects parallel with the magnetic field direction may be overlooked. In order to overcome this, a non-destructive testing method based on magneto-optical imaging under a vertical combined magnetic field (VCMF) is proposed. To demonstrate this, the experimental results of the magneto-optical imaging of weld defects excited by a vertical combined magnetic field (VCMF) or parallel combined magnetic field (PCMF) are compared with those of traditional magnetic fields (constant magnetic field (CMF), alternating magnetic field (AMF), and rotating magnetic field (RMF)). It is found that the magneto-optical imaging under a VCMF can accurately detect weld defects of any shape and distribution. In addition, the center difference method is used to eliminate the influence of noise on the defect contour extraction of magneto-optical images, and the active contour of weld defects in the magneto-optical images is extracted. The results show that many noises can be identifiedby the robustness of the level set method, operating in low-pass filtering, so that much information that is usually lost can be retained.