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.

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.

The existing magneto-optical imaging of weld defects is carried out under a constant magnetic field or alternating magnetic field. The magneto-optical image (MOI) is easy to saturate under a constant magnetic field, resulting in the loss of defect information. It is very difficult to realize magneto-optical imaging of micro-defects under alternating magnetic fields. Therefore, magneto-optical imaging under a combined magnetic field is proposed in this article. Firstly, the effect of dynamic permeability on the law of magnetization of defects is analyzed. Then, through simulation experiments, the magnetic flux leakage law of defect samples under constant magnetic field, alternating magnetic field, and combined magnetic field are analyzed. Finally, the magneto-optical imaging experiment is used to study the imaging law of wire cutting grooves under different magnetic field excitation. The experimental results show that compared with constant magnetic field and alternating magnetic field, the difference of leakage magnetic field under combined magnetic field excitation is more obvious. This shows that using a combined magnetic field for imaging detection can effectively improve the disadvantage that it is difficult to realize an MOI of micro-defects under an alternating magnetic field.

Magneto-optical imaging is based on the theory of leakage magnetic field and the Faraday magneto-optical effect. A magnetic dipole model of pit was established and verified by comparing with gray value of magneto-optical image of pit. The sag, pit, non-melting and non-defect of welded pieces made in the detection of magneto-optical were simulated by the two-dimensional finite element models. The magnetic induction intensity distributions of defects in the lift strength of 1mm were obtained in the simulations. Experiments on detecting the defects referred above by magneto-optical detection were carried out and magneto-optical images of the defects were acquired. The simulations were proved reliable when compared with magnetic field distribution of models and gray curves of magneto-optical images of the corresponding defects. Also, these models analyzed magnetic induction intensity distributions of different defects in different strengths of lift. Furthermore, it provided the theoretical and experimental basis for further study of the mechanism of magneto-optic imaging.

In the field of magneto-optical imaging nondestructive testing for welding defects, multi-angle detection of welding defects has already been achieved. However, research on automatic defect recognition and contour extraction remains insufficient. Therefore, to enable automatic detection of welding defects using magneto-optical imaging technology, it is essential to address the key issues of defect recognition and contour extraction in magneto-optical images. The dataset in this article includes five types of images: defect-free, lack-of-fusion, cracks, pits, and Weld reinforcement. Firstly, the Mask R-CNN detection method is used to perform defect recognition and contour segmentation on the original magneto-optical image dataset. The detection results indicate that the recognition rate of lack-of-fusion and Weld reinforcement in the original magneto-optical image is not high, and the recognition accuracy of pits and cracks is extremely low. Subsequently, the magneto-optical image dataset was preprocessed using the differential level set method, and the mask R-CNN algorithm was used to identify defect types and segment defect contours. Comparing the results of two experiments, it was found that the detection accuracy of the preprocessed dataset was higher, and the overall recognition accuracy increased by $30\%$.

In laser-MIG hybrid welding, the visual information can be used to monitor the stability of the process and estimate the weld formation. Taking the hybrid welding of ER308 stainless steel as an example, a high-speed camera is used to simultaneously obtain visual information of top and bottom of the weldment during the welding process. Combined with the visual characteristics of arc light, molten hump and spatter at the bottom, the influence of various welding state characteristics on weld formation was analyzed. The comparison between the welding process of good weld and root humps illustrated that the time series curves of the area and centroid coordinates of the molten hump at the bottom can reflect the formation process of the root humps. The main cause of root humps is the lack of heat input. The results support a basis for monitoring and controlling the laser–MIG hybrid welding process status.