Search Results (446)

We report on the welding of optical borosilicate glass to an unpolished copper substrate (surface Ra of 0.27 µm and Rz of 1.89 µm) using bursts of femtosecond laser pulses. The present paper puts forth the hypothesis that glass–metal welding with a gap is contingent upon the ejection of molten jets of glass. We have ascertained the impact of pulse energy and focal position on weldability. This finding serves to substantiate our initial hypothesis and provides a framework for understanding the conditions under which this hypothesis is applicable. Under optimal conditions, but without the assistance of any clamping system, our welded samples maintained a breaking resistance of up to 10.9 MPa. Full article

Accurate weld defect detection is critical for ensuring structural safety and evaluating welding quality in industrial applications. Manual inspection methods have inherent limitations, including inefficiency and inadequate sensitivity to subtle defects. Existing detection models, primarily designed for natural images, struggle to adapt to the characteristic challenges of weld X-ray images, such as high noise, low contrast, and inter-defect similarity, particularly leading to missed detections and false positives for small defects. To address these challenges, a multi-dimensional feature fusion model (MADet), which is a multi-branch deep fusion network for weld defect detection, was proposed. The framework incorporates two key innovations: (1) A multi-scale feature fusion network integrated with lightweight attention residual modules to enhance the perception of fine-grained defect features by leveraging low-level texture information. (2) An anchor-based feature-selective detection head was used to improve the discrimination and localization accuracy for five typical defect categories. Extensive experiments on both public and proprietary weld defect datasets demonstrated that MADet achieved significant improvements over the state-of-the-art YOLO variants. Specifically, it surpassed the suboptimal model by 7.41% in mAP@0.5, indicating strong industrial applicability. Full article

Non-uniform temperature fields are developed during the welding of studs in steel–concrete composite bridges. Due to uneven thermal expansion and reversible solid-state phase transformations between ferrite/martensite and austenite structures within the materials, residual stresses are induced, which ultimately degrades the mechanical performance of the structure. For a better understanding of the influence on steel–concrete composite bridges’ structural behavior by residual stress, accurate simulation of the spatio-temporal temperature distribution during stud welding under practical engineering conditions is critical. This study introduces a precise simulation method for temperature evolution during stud welding, in which the Gaussian heat source model was applied. The simulated results were validated by real welding temperature fields measured by the infrared thermography technique. The maximum error between the measured and simulated peak temperatures was 5%, demonstrating good agreement between the measured and simulated temperature distributions. Sensitivity analyses on input current and plate thickness were conducted. The results showed a positive correlation between peak temperature and input current. With lower input current, flatter temperature gradients were observed in both the transverse and thickness directions of the steel plate. Additionally, plate thickness exhibited minimal influence on radial peak temperature, with a maximum observed difference of 130 °C. However, its effect on peak temperature in the thickness direction was significant, yielding a maximum difference of approximately 1000 °C. The thermal influence of group studs was also investigated in this study. The results demonstrated that welding a new stud adjacent to existing ones introduced only minor disturbances to the established temperature field. The maximum peak temperature difference before and after welding was approximately 100 °C. Full article

This study aims to address the challenges posed by uneven energy amplitude and a low signal-to-noise ratio (SNR) in the total focus imaging of coarse-crystalline elastic anisotropic materials. A novel method for acoustic field correction vector-coherent total focus imaging, based on the materials’ properties, is proposed. To demonstrate the effectiveness of this method, a test specimen, an austenitic stainless steel nozzle weld, was employed. Seven side-drilled hole defects located at varying positions and depths, each with a diameter of 2 mm, were examined. An ultrasound simulation model was developed based on material backscatter diffraction results, and the scattering attenuation compensation factor was optimized. The acoustic field correction function was derived by combining acoustic field directivity with diffusion attenuation compensation. The phase coherence weighting coefficients were calculated, followed by image reconstruction. The results show that the proposed method significantly improves imaging amplitude uniformity and reduces the structural noise caused by the coarse crystal structure of austenitic stainless steel. Compared to conventional total focus imaging, the detection SNR of the seven defects increased by 2.34 dB to 10.95 dB. Additionally, the defect localization error was reduced from 0.1 mm to 0.05 mm, with a range of 0.70 mm to 0.88 mm. Full article

In response to the challenges associated with weld treatment during the on-site corrosion protection of hydraulic steel gates, this paper proposes a method utilizing a magnetic adsorption climbing robot to perform corrosion protection operations. Firstly, a magnetic adsorption climbing robot with a multi-wheel independent drive configuration is proposed as a mobile platform. The robot body consists of six joint modules, with the two middle joints featuring adjustable suspension. The joints are connected in series via an EtherCAT bus communication system. Secondly, the kinematic model of the climbing robot is analyzed and a PID trajectory tracking control method is designed, based on the kinematic model and trajectory deviation information collected by the vision system. Subsequently, the proposed kinematic model and trajectory tracking control method are validated through Python3 simulation and actual operation tests on a curved trajectory, demonstrating the rationality of the designed PID controller and control parameters. Finally, an intelligent software system for weld defect detection based on computer vision is developed. This system is demonstrated to conduct defect detection on images of the current weld position using a trained model. Full article

Based on the engineering background of a new type of segmental-assembled steel temporary beam buttress, the fatigue strength evaluation method of the steel box girders with open longitudinal ribs was taken as the research objective. The fatigue stress calculation analysis and the full-scale fatigue loading test for the steel box girder local component were carried out. The accuracy of the finite-element model was verified by comparing it with the test results, and the rationality of the fatigue strength evaluation methods for welded joints was deeply explored. The results indicate that the maximum nominal stress occurs at the weld toe between the transverse diaphragm and the top plate at the edge of the loading area, which is the fatigue-vulnerable location for the steel box girder local components. The initial static-load stresses at each measuring point were in good agreement with the finite-element calculation results. However, the static-load stress at the measuring point in the fatigue-vulnerable position shows a certain decrease with the increase in the number of cyclic loads, while the stress at other measuring points remains basically unchanged. According to the finite-element model, the fatigue strengths obtained by the nominal stress method and the hot-spot stress method are 72.1 MPa and 93.8 MPa, respectively. It is reasonable to use the nominal stress S-N curve with a fatigue life of 2 million cycles at 70 MPa and the hot-spot stress S-N curve with a fatigue life of 2 million cycles at 90 MPa (FAT90) to evaluate the fatigue of the welded joints in steel box girders with open longitudinal ribs. According to the equivalent structural stress method, the fatigue strength corresponding to 2 million cycles is 94.1 MPa, which is slightly lower than the result corresponding to the main S-N curve but within the range of the standard deviation curve. The research results of this article can provide important guidance for the anti-fatigue design of welded joints in steel box girders with open longitudinal ribs. Full article

Process control and quality assurance of wire + arc additive manufacturing (WAAM) and automated welding rely heavily on in-process monitoring videos to quantify variables such as melt pool geometry, location and size of droplet transfer, arc characteristics, etc. To enable feedback control based upon this information, an automatic and robust segmentation method for monitoring of videos and images is required. However, video segmentation in WAAM and welding is challenging due to constantly fluctuating arc brightness, which varies with deposition and welding configurations. Additionally, conventional computer vision algorithms based on greyscale value and gradient lack flexibility and robustness in this scenario. Deep learning offers a promising approach to WAAM video segmentation; however, the prohibitive time and cost associated with creating a well-labelled, suitably sized dataset have hindered its widespread adoption. The emergence of large computer vision models, however, has provided new solutions. In this study a semi-automatic annotation tool for WAAM videos was developed based upon the computer vision foundation model SAM and the video object tracking model XMem. The tool can enable annotation of the video frames hundreds of times faster than traditional manual annotation methods, thus making it possible to achieve rapid quantitative analysis of WAAM and welding videos with minimal user intervention. To demonstrate the effectiveness of the tool, three cases are demonstrated: online wire position closed-loop control, droplet transfer behaviour analysis, and assembling a dataset for dedicated deep learning segmentation models. This work provides a broader perspective on how to exploit large models in WAAM and weld deposits. Full article

Background/Objectives: Additive manufacturing (AM) enables the production of cementless acetabular cups with porous surfaces that facilitate early osseointegration. Directed energy deposition (DED), a form of AM, allows the direct welding of porous structures onto metal substrates without requiring a vacuum environment, offering advantages over conventional powder bed fusion methods. Despite growing interest in DED, no prospective clinical studies evaluating DED-based acetabular components have been published to date. This study assessed short-term outcomes of a DED-based 3D-printed acetabular cup in total hip arthroplasty (THA). Methods: A total of 120 patients who underwent primary cementless THA using the Corentec Mirabo Z^® acetabular cup were prospectively enrolled. Among them, 124 hips from 100 patients who had completed a minimum of 24 months of follow-up were included in the analysis. Clinical outcomes were assessed using the Harris hip score (HHS), WOMAC, EQ-5D-5L, and pain NRS. Radiographic evaluation included measurements of cup position, osseointegration, and detection of interfacial or polar gaps on CT and plain radiographs. Implant-related complications were also recorded. Results: At a mean follow-up of 34.6 months, the implant survival rate was 99.3%, with one revision due to suspected osseointegration failure. The HHS improved from 56.6 to 91.4 at 24 months, and the NRS decreased from 6.2 to 1.1 (both p < 0.001). Interfacial gaps were observed in 58.1% of cases on CT, though most were <1 mm and not clinically significant. Common postoperative issues included greater trochanteric pain syndrome, squeaking, and iliotibial band tightness, all of which were resolved with conservative treatment. Conclusions: DED-based 3D-printed acetabular cups demonstrated favorable short-term clinical and radiographic outcomes, with high survivorship and reliable early osseointegration in cementless THA. Full article

This research provides a detailed investigation into the mechanical properties and microstructural evolution of heat-resistant steel P92 subjected to both initial (i) welding procedures and simulated (ii) repair welding. The study addresses the influence of critical welding parameters, including preheating temperature, heat input, and post-weld heat treatment (PWHT), with a particular emphasis on the metallurgical consequences arising from the application of repair welding thermal cycles. Through the analysis of three welding probes—initially welded pipes using the PF (vertical upwards) and PC (horizontal–vertical) welding positions, and a PF-welded pipe undergoing a simulated repair welding (also in the PF position)—the research compares microstructure in the parent material (PM), weld metal (WM), and heat-affected zone (HAZ). Recognizing the practical limitations and challenges associated with achieving complete removal of the original WM under the limited (in-field) repair welding, this study provides a comprehensive comparative analysis of uniaxial tensile properties, impact toughness evaluated via Charpy V-notch testing, and microhardness measurements conducted at room temperature. Furthermore, the research critically analyzes the influence of the complex thermal cycles experienced during both the initial welding and repair welding procedures to elucidate the practical application limits of this high-alloyed, heat-resistant P92 steel in demanding service conditions. Full article

Boron steel welded tubes show strong potential as blanks in the integrated hot gas forming–quenching process for fabricating complex thin-walled automotive parts. Nonetheless, the non-uniform characteristics of the base metal and the weld in the high-heat welded tube can result in uneven deformation during the bulging process. This inconsistency hampers precise predictions of the deformation behavior of the welded tubes at high temperatures. Accordingly, this research explored the flow characteristics and mechanical properties of PHS1500 boron steel welded tubes. This research was conducted at 850 °C and 900 °C, with strain rates of 0.01 s⁻¹–1 s⁻¹. The Johnson–Cook model was modified for both the base metal and the weld using experimental stress–strain data. Meanwhile, to assess the model precisions, the correlation coefficient r and the average absolute relative error (AARE) were employed. Finally, hot gas forming of PHS1500 boron steel welded tubular parts with complex shapes was predicted through a finite element analysis. This research showed a positive correlation of the strain rate with both the yield and tensile strengths in the base metal and the weld. The average yield strength and tensile strength of the weld were 12.8% and 3.9% higher than those of the base metal, respectively. The r and AARE of the modified Johnson–Cook constitutive model for the base metal’s and the weld’s flow stress were 0.99 and 2.23% and 0.982 and 5.31%, respectively. The maximum deviation in the predictions of the distribution of the wall thickness of a typical cross-section of the formed complex-shaped tubular parts was less than 8%. Full article

Welding robots play a crucial role in manufacturing industries, where minimizing energy consumption (EC) is increasingly important for enhancing efficiency and reducing operational costs. This study presents a data-driven approach to model and optimize EC in welding robot systems, utilizing a dataset generated from real-world measurements of robot EC during various motions and integrated with trajectory data. A predictive model was developed using an extreme gradient boosting (XGBoost) regression technique focused on joint torque data, which achieved a mean absolute percentage error (MAPE) of 1.86%. Furthermore, trajectory optimization was achieved by adjusting the spatial position of the workpiece, effectively reducing EC. To solve the optimization problem, an improved whale optimization algorithm (IWOA) was employed. Experimental validations with a welding robot demonstrate that the proposed method not only accurately predicted EC with a MAPE of 2.66% but also reduced the robot system’s EC by 6.72%, outperforming the traditional method focused solely on joint motor EC, which achieved a 4.08% reduction. These results confirm the efficacy of the proposed approach, underscoring its potential for broad application in robotic systems to achieve significant energy savings. Full article

Ultrasonic welding, as a solid-state connection technology, has attracted considerable attention. The traditional ultrasonic welding sonotrode is not conducive to the study of the bonding mechanism of a straight interface, while the ultrasonic additive sonotrode does not have this problem. In this study, a special ultrasonic welding sonotrode was designed to form the joint, which is identical to ultrasonic additive manufacturing, to reveal its interfacial bonding mechanism between layers. Firstly, the linear metallurgical bonding density (LMD) of the joint is found to be positively correlated with welding time and negatively with welding pressure. Furthermore, the joint interface undergoes recrystallization after intense plastic deformation, with the obstruction of surface deformation by interface block resulting in the formation of a non-straight interface, which is beneficial to the formation of metallurgical bonding. Finally, a new concept of “Interface Block” was proposed, which can be applied to explain the formation of metallurgical bonding at the interface in ultrasonic additive manufacturing. Full article

Wire and arc additive manufacturing (WAAM) is a promising method of producing medium- and large-sized aluminum alloy structures, though it faces challenges such as porosity, residual stresses and inconsistent mechanical properties. This study investigates the effect of current type (AC and DC MIG welding) and polarity balance (influencing the duration of the positive/negative period of the cycle) on the mechanical and microstructural properties of 6063 aluminum alloy walls produced by WAAM. A TiB₂-refined Al–Mg–Si (6063) filler wire, specifically developed for arc-based processing, was used. Tensile tests, Vickers hardness measurements (HV5), optical microscopy and X-ray diffraction based on cosα method were used to evaluate performance in terms of strength, ductility, hardness, grain structure, porosity and residual stress. The results showed that the balance of AC polarity significantly affects wall geometry, porosity and grain structure. Increasing the negative polarity period resulted in taller and narrower walls, while the widest walls were produced with increased positive polarity. Residual stress measurements revealed a tensile–compressive–tensile distribution, with the DC-MIG samples showing the highest surface stress values. The highest tensile strength (172 MPa) was measured in the lower region of the DC-MIG sample, suggesting that areas near the substrate benefit from faster cooling. Full article

Joining steel and Al alloys can fully utilize their advantages for both base metals (BMs) and optimize automobile structures. In this study, the laser welding–brazing technique was utilized to join DP780 steel and aluminum alloy 5754 (AA5754). The mechanical properties, microstructure, and fracture locations of steel–Al joints prepared using different laser spot positions were comparatively investigated. As the proportion of the laser spot on the steel BM increased from 50% to 90%, the tensile–shear strength of the steel–Al welded joint rose from 169 MPa to 241 MPa. Meanwhile, the fracture location of the joint shifted from the interface to the BM of the aluminum alloy. The change in the laser spot position could dramatically affect the interfacial microstructure and fracture mode of the steel–Al joint. When the proportion of the laser spot on the steel BM was relatively small (50%), the growth of intermetallic compounds (IMCs) was inhibited. The metallurgical bonding effect at the steel–Al interface was poor. In this case, the interfacial zone became the primary path for the crack propagation. Thus, interface failure became the dominant failure mode of the steel–Al joint. On the contrary, metallurgical bonding at the interface was remarkably improved as the proportion of the laser spot on the BM of the steel increased (to 90%). It was determined that the IMCs could effectively hinder the propagation of cracks along the interface. Eventually, the joint fractured in the Al alloy’s BM, resulting in a qualified steel–Al joint. Full article

To address the challenges of redundant point cloud processing and insufficient robustness under complex working conditions in existing teaching-free methods, this study proposes a dual-modal perception framework termed “2D image autonomous recognition and 3D point cloud precise planning”, which integrates stereo vision and deep learning. First, an improved U-Net deep learning model is developed, where VGG16 serves as the backbone network and a dual-channel attention module (DAM) is incorporated, achieving robust weld segmentation with a mean intersection over union (mIoU) of 0.887 and an F1-Score of 0.940. Next, the weld centerline is extracted using the Zhang–Suen skeleton refinement algorithm, and weld feature points are obtained through polynomial fitting optimization to establish cross-modal mapping between 2D pixels and 3D point clouds. Finally, a groove feature point extraction algorithm based on improved RANSAC combined with an equal-area weld bead filling strategy is designed to enable multi-layer and multi-bead robot trajectory planning, achieving a mean absolute error (MAE) of 0.238 mm in feature point positioning. Experimental results demonstrate that the method maintains high accuracy under complex working conditions such as noise interference and groove deformation, achieving a system accuracy of 0.208 mm and weld width fluctuation within ±0.15 mm, thereby significantly improving the autonomy and robustness of robot trajectory planning. Full article