Welding in the World最新文献

Welding of AlSi10Mg alloys fabricated by additive manufacturing (AM) has been recently conducted to meet the demands for joining or repairing them. However, high susceptibility to porosity occurring in weld metal (WM) poses a significant challenge for fusion welding of AM AlSi10Mg alloys. The laser metal deposition (LMD) process has emerged as a promising welding solution due to its low dilution rate for reducing the porosity. In this study, LMD welding of AM AlSi10Mg alloys was carried out employing different heat inputs with five and eight tracks. The study systematically assessed the impact of heat input on porosity, microstructure, and mechanical properties of the welded joints. The results show that the decrease of heat input from 180 to 75 J/mm results in a substantial reduction in porosity from 7.0 to 2.1%. This reduction leads to a 29.4% increase in ultimate tensile strength (UTS) and an 11.7% increase in elongation index (EI). Furthermore, the upper region of joints with eight tracks possessing low heat input displays lower porosity and superior mechanical properties than the bottom region with relatively high heat input. The WM with eight tracks exhibits refined α-Al cells and Si-rich eutectic phases, improved connectivity of Si-rich networks, and increased solid solution strengthening, compared to the five-track joints with higher heat input. As a result, low heat input of the upper region in the LMD welded joints has been effective in minimizing hydrogen pores, enhancing WM microstructure, and improving the mechanical properties of welded joints in AM AlSi10Mg alloys.

Weld defect detection is an important task in the welding process. Although there are many excellent weld defect detection models, there is still much room for improvement in stability and accuracy. In this study, a lightweight deep learning model called WeldNet is proposed to improve the existing weld defect recognition network for its poor generalization performance, overfitting, and large memory occupation, using a design with a small number of parameters but with better performance. We also proposed an ensemble-distillation strategy in the training process, which effectively improved the accuracy rate and proposed an improved model ensemble scheme. The experimental results show that the final designed WeldNet model performs well in detecting weld defects and achieves state-of-the-art performance. Its number of parameters is only 26.8% of that of ResNet18, but the accuracy is 8.9% higher, while achieving a 24.2 ms inference time on CPU to meet the demand of real-time operation. The study is of guiding significance for solving practical problems in weld defect detection, and provides new ideas for the application of deep learning in industry. The code used in this article is available at https://github.com/Wanglaoban3/WeldNet.git.

Keyhole Tungsten inert gas (K-TIG) welding can realize single-sided welding and double-sided forming. However, due to the influence of gravity, undercuts always occur in K-TIG horizontal welding. In order to expand the application scenarios of K-TIG and achieve automatic welding, a magnetic controlled K-TIG horizontal automatic welding system is proposed in this paper. A longitudinal magnetic field is used to weaken the influence of gravity and improve welding quality. The OCR (Object-Contextual Representations)-SVM (support vector machines) model is proposed to identify the welding penetration states during K-TIG horizontal welding, whose accuracy rate is 93%. In order to solve the problem of slow convergence and poor learning of difficult-to-learn classes, a loss function called Unified Focal loss was used, which achieves a mIoU (the mean of Intersection over Union) score of 91.48%.

Using different rotational speeds in friction stir welding is a new way to improve the microstructure and the impact toughness of the weld. However, the specific speed most suitable for Q1100 ultra-high strength steel has yet to be discovered. Here, friction stir welding of 8 mm thick Q1100 ultra-high strength steel was carried out at constant welding speeds of 375 rpm, 475 rpm, and 600 rpm. With the aid of an optical microscope, a microhardness tester, an impact tester, a tensile tester, and a field emission scanning electron microscope (SEM) equipped with an electron backscatter diffraction (EBSD) system, the microstructure characteristics such as the carbide precipitation phase in the original austenite grains, the dislocation pattern within the martensitic lath, and the fracture morphology of the impact specimens were analyzed. The results show that the overall hardness and impact toughness of the advancing side and retreating side of the stirring zone show a trend of first increasing and then decreasing with the increase of the rotational speed, in which the hardness value of the advancing side of the same speed is higher than that of the retreating side. In contrast, the impact toughness is higher on the retreating than on the advancing side. At 375 rpm, the carbide is needle-like, the martensite bundle is narrow, and there are more high-angle grain boundaries, the hindrance to crack expansion is significant, and the toughness is higher relative to the base material. At 475 rpm, the martensite bundle widens, the number of high-angle grain boundaries increases, both the advancing and retreating sides are ductile fractures with small tearing dimples of varying sizes distributed around the large tearing dimples, and the toughness increases relative to 375 rpm. When the speed at 600 rpm, the carbide is coarser, the martensite bundle is more expansive than at 475 rpm, the number of high-angle grain boundaries is reduced, the tearing toughness dimples are unevenly distributed, and the toughness is reduced. Compared to 375 rpm and 600 rpm, the joint cooling rate is either faster or slower, and the 475 rpm cooling rate is just right in between. Meanwhile, when the rotational speed at 475 rpm, the average hardness of the joint is 375 HV, the impact work at − 40℃ is 51 J, and its tensile strength and elongation are 998 MPa and 3.09%, respectively, with the best comprehensive mechanical properties.

In this work, the technical feasibility of micro-friction stir lap welding to join 0.5-mm ultra-thin aluminium and copper sheets was studied. After identifying the processability windows of important parameters such as plunge depth, welding speed and material positioning, the effect of welding speed to join the ultra-thin AA5052 and C11000 sheets was assessed. Welding speeds were varied from 50 to 400 mm/min. The relationship of the welding speed to the joint quality, such as microstructure, tensile lap shear strength, weld surface roughness and joint electrical resistance was elucidated. It was found that the dissimilar sheets only joined when the copper sheet was placed on top of the aluminium sheet. Feasible welding was found at welding speeds of 50 mm/min and 70 mm/min, a constant rotational speed of 1500 rpm and a plunge depth of 0.55 mm. The welds possessed similar average tensile lap shear strength of 16 to 18 MPa but differed in microstructure and joint electrical resistance. More visible stir zones with lamella bands were found in the microstructure of welds produced at 50 mm/min, indicating a higher degree of mixing, albeit with excessive flashes and tunnel defects near the joint interface. On the other hand, the welds produced at 70 mm/min exhibited limited mixing and lamellar intermetallic compounds. Tunnel defects were mostly at the advancing side within the copper layer, and hook defects were absent. With selected processing parameters, micro-friction stir welding ultra-thin copper sheets to aluminium sheets is demonstrably feasible for less critical applications.

A transient 3D numerical model was established to investigate the multi-coupling transport phenomena in the Al-alloy GMAW bead-on-plate welding process. An integrated self-adaptive distribution mode of “arc current density-arc pressure-electromagnetic force-arc heat” was proposed to adapt to the evolution of the surface morphology of the molten pool. The heat and force state of the molten pool was analyzed to investigate its influence on the bead formation. The results showed that the arc pressure and droplet impingement promoted the backward flow of the liquid metal, thus forming the gouging region. It decreased the concentration of the arc current density, thereby reducing the superheat of the liquid metal and facilitating the filling of the weld toe. Based on the characteristics of the temperature and velocity fields, the characteristics of weld formation in the three stages of arc preheating, melting, and solidification were analyzed. This study revealed the relationship between molten pool behavior and bead formation, promoting the implementation of Al-alloy GMAW in welding and additive manufacturing.

Changing process conditions such as distortion, varying seam preparation or gap width during welding is a major challenge in automated gas metal arc welding (GMAW). While human welders can adjust the process during welding (e.g. welding speed, torch orientation), an automated welding system needs sensors to detect and actuators to adjust the process. Adjusting the process in response to changing process conditions is usually referred to as adaptive welding. The aim of this work is to build a robotic welding system capable of automatically adapting the welding process using some of the approaches of a human welder. To enable adaptive process control, a robotic welding system is built. It consists of four main components: a six-axis industrial robot for mechanical guidance of the welding torch, a welding power source, a monochrome visual camera as an image sensor and a process controller that combines the three components. The camera captures images of the weld pool during welding and processes the images to provide geometrical information such as the width of the weld pool and the position of the weld pool front. Changes in the weld pool geometry are quantified, and an adjustment strategy is generated in the process control unit in real time. Process adjustments can be mechanical (e.g. welding speed, torch orientation) and electrical by adjusting synergic process settings (wire feed speed, arc length, process dynamics). Validation tests demonstrate the functionality of the welding system. Two use cases were investigated. Firstly, a deposited weld bead was examined, and variations in the width of the weld pool were induced by varying the welding speed. The second application was a seam tracking application. The path is pre-programmed, and the specimen is positioned with an offset to the path. Compensation for the offset is implemented.

The present work investigates the high-temperature tensile and creep properties of the dissimilar metal weld joints of 304L austenitic stainless steel (SS) and P92 creep strength-enhanced ferritic-martensitic (CSEF/M) steel under different testing condition. Thermanit MTS 616 filler rod (P92 filler) and the multi-pass tungsten inert gas (TIG) welding process were used to create the dissimilar weld connection. The ultimate tensile strength (UTS) was evaluated in the temperature range of 450–850 °C. Creep testing was conducted at a temperature of 650 °C while applying stress levels of 130 MPa, 150 MPa, 180 MPa, and 200 MPa. The shortest creep life (2.53 h) was recorded for the specimen tested at 650 °C and subjected to 200 MPa, whereas the longest creep life (~ 242 h) was observed for the specimen tested at 650 °C with a stress of 130 MPa. The linear regression model was developed using an applied stress (σ) v/s rupture time (t_R) plot at 650 °C. The applied stress and rupture time followed the logarithmic equation: log(t_R) = 22.57566 + (-9.55294) log (σ). The detailed microstructural characterization and micro-hardness distribution across the fractured specimens was carried out. The findings demonstrated that the service life span of this weld joint at high temperature and stress conditions is influenced by the undesired microstructural changes at elevated temperature, such as coarsening of the precipitates, development of the Laves phase, softening of the matrix, and strain-ageing phenomenon.

Increasing requirements in terms of weight, safety, and economy are leading to the use of high-strength steels in automotive construction. The focus is on advanced high-strength steels (AHSS). In chassis applications, complex-phase (CP) steels are frequently used and usually processed uncoated. But the demand for galvanized sheet steel is rising steadily to meet the increasing corrosion protection requirements of automotive manufacturers. Gas metal arc welding (GMAW) is an established joining technology. A typical joint geometry for welded chassis structures is the lap joint. The zinc coating poses a particular challenge in the welding process, especially for this geometry. As a result of its low boiling point, the zinc coating evaporates during welding and can lead to pores in the weld seam. Dynamic (crash) loads play a special role in the design of safety-relevant components in automotive engineering. The dynamic strength of tensile shear specimens made of hot-dip zinc-coated CP steel with a sheet thickness of t = 2.5 mm is presented in this paper, considering the influencing variables of heat input, specimen geometry, and pore content. The results of high-speed tensile tests with a servo-hydraulic high-speed testing machine for the test velocities 0.00017 m/s, 0.05 m/s, 0.5 m/s, and 5 m/s according to SEP 1231 are presented. In addition, the failure behavior of the shear tensile specimens welded as fillet welds by GMAW is analyzed by digital image correlation (DIC), and the resulting fracture mechanisms are investigated and presented by scanning electron microscope (SEM).