To explore the crack formation mechanism of solid self-piercing riveted joints of Mg/Al dissimilar alloys, the mechanical properties of the magnesium alloy materials were characterized. The material constitutive model and GISSMO fracture failure model of the magnesium alloy were constructed, and a refined simulation model for the forming process of solid self-piercing riveting was established. The strain field distribution and material flow characteristics during the joint forming process were analyzed; the internal crack formation mechanism of the joint was revealed, and crack suppression was achieved through die structure optimization. The simulation and experimental results indicate that cracks are mainly generated in the piercing and extrusion stages of the riveting process; crack sources are initiated in the lower magnesium alloy sheet near the inner and outer edges of the die boss and the dissimilar material interface; under the combined extrusion of the punch and die boss, the crack sources on the upper and lower surfaces of the magnesium alloy sheet propagate towards each other and finally form macroscopic “bowl-shaped” cracks. The optimized beveled die reduces the peak effective plastic strain in the dangerous area, slows down the material flow rate, suppresses the generation of joint cracks, improves the material filling performance in the mechanical interlock region, and realizes the efficient and reliable joining of Mg/Al dissimilar alloys.
Laser welding technology has significant advantages in the precision machining and mass production of metal bipolar plates for fuel cells due to its characteristics of high precision and high efficiency. However, in the welding of ultra-thin metal bipolar plates, problems such as difficult-to-control weld quality and welding thermal deformation exist. To solve the above problems and optimize the welding process window more efficiently, a Gaussian surface-cylinder compound heat source model based on the non-penetrating welding of ultra-thin metal bipolar plates was constructed using COMSOL Multiphysics. A full factorial analysis scheme with four factors and five levels was constructed by adopting three parameters: penetration depth, weld width, and joint width. A BP neural network model was trained through JMP software combined with the actual weld pool morphology, making the modified simulation model closer to the actual welding weld pool. The test results show that when the modified laser heat source model is used for the welding process simulation, and the simulation results are compared with the actual bipolar plate welding test results, the relative errors between the simulation data and the test data are all within ±5%. This indicates that the model can well guide the actual engineering practice of the laser welding process for metal bipolar plates in the future.
To investigate the effects of different oscillation paths (no oscillation, 8-shaped, and triangular types) on the interface microstructure, intermetallic compound (IMC) layer thickness, tensile strength, and fracture behavior of Al/Ti dissimilar metal joints during the laser welding-brazing process, Al/Ti composite joints were prepared by laser welding-brazing technology. By using the oscillation path of the laser spot as the key process variable, the weld morphology and interface microstructure were characterized by optical microscopy, scanning electron microscopy, and energy dispersive spectroscopy. Moreover, the mechanical properties and fracture mechanism of the joints were analyzed in combination with tensile tests. The results indicate that, compared with no oscillation, the 8-shaped and triangular oscillation paths can effectively increase the spreading length of the brazing filler metal on the surface of the Ti alloy and significantly inhibit the growth of interfacial IMC. Under the 8-shaped oscillation, the interfacial IMC thickness is the thinnest, ranging from 0.9 to 3.19 μm. element analysis confirms that Si aggregates at the Ti/Al interface, forming a Ti(Al, Si)3 ternary phase. In terms of mechanical properties, the tensile strength of the joint without oscillation is the lowest (119.19 MPa). The fracture occurs at the thicker Ti/Ti(Al, Si)3 interface or the Ti(Al, Si)3 layer, presenting typical brittle fracture characteristics. The oscillation paths effectively improve the joint strength by refining the IMC layer.
To address the problems of rotated objects, multiple scales, and large aspect ratios encountered in the coarse positioning of weld seams during welding automation, a coarse positioning method for weld seams based on an improved YOLOv11 oriented bounding box (YOLOv11-OBB) model was proposed. First, an OBB-RLSCD detection head was designed to capture rotational features using a combination of depthwise convolution and pointwise convolution, accurately capturing rotational features under a lightweight architecture and improving the detection efficiency and accuracy. Second, an adaptive lightweight downsampling module was adopted to improve the convolution, effectively retaining the key features of weld seams while reducing the amount of computation. Additionally, dynamic convolution was integrated into the C3k2 module to enable the convolution operation to adaptively adjust according to the input features. Finally, the PIoU loss function was introduced to optimize the positioning accuracy of rotated objects at the pixel level, enhancing the adaptability to complex scenes. The results indicate that the mean average precision of the model reaches 86.5%, which is higher than that of the original YOLOv11-OBB model; the number of parameters is reduced; the computation amount is reduced, and the inference speed reaches 89.7 frames/s, which meets the demand for real-time coarse positioning of welding robots. Meanwhile, the model is validated on the public dataset NEU-DET, and it still maintains high detection accuracy, which proves that the algorithm has good adaptability in different industrial scenarios.
Welding a lifting-eye plate onto underwater structures such as sunken ships to serve as anchoring points for underwater salvage can significantly improve salvage efficiency and reduce operational time. Under unmanned collaboration conditions, the welding robot needs to autonomously acquire the three-dimensional information of the lifting-eye plate and determine the welding position. Therefore, a three-dimensional reconstruction and welding guidance method for the lifting-eye plate based on instant neural graphics primitives (Instant-NGP) was proposed. Multi-view images of the lifting-eye plate were captured in an underwater hyperbaric dry chamber environment by a depth camera mounted on the welding robot, and the Instant-NGP algorithm was utilized to perform three-dimensional reconstruction within a large field of view. The three-dimensional point cloud of the lifting-eye plate was extracted, filtered, registered, coordinate-transformed, and mapped to the robot base coordinate system. The LO-RANSAC algorithm was used to perform planar segmentation on the point cloud on both sides of the weld groove; the weld seam centerline was obtained by calculating the intersection line of the fitted planes on both sides, and the trajectory starting point was determined by combining the point cloud boundary range of the groove region, thereby generating the initial welding guidance trajectory. Welding guidance and accuracy verification experiments were conducted through an experimental platform. The experiments indicate that the method can effectively accomplish the initial welding guidance; the average errors of the trajectory starting point in the x, y, and z directions are 1.17 mm, 1.09 mm, and 1.36 mm, respectively, meeting the requirements for the initial welding guidance of the underwater lifting-eye plate.
