Welding System Research Articles

АСИНХРОННІ ГЕНЕРАТОРИ В АВТОНОМНИХ ДЖЕРЕЛАХ ЖИВЛЕННЯ ЗВАРЮВАЛЬНОЇ ДУГИ. СТАН І ПЕРСПЕКТИВИ

The article is aimed at generalizing the results of the study of asynchronous generators (AG) of autonomous welding arc power sources (AWPS) obtained in the Department of Electromechanical Systems of the Institute of Electrodynamics of the NASU. The proposed classification of AG of autonomous welding systems is considered, mathematical models are developed, the results of computational and experimental studies of such systems with AG with capacitor excitation and an uncontrolled rectifier, in the DC circuit of which high-frequency inverters, pulse-width regulators or half-bridge inverters are connected, as well as generators with valve and valve-capacitor excitation. The design features and experimental samples of welding arc power sources with AG are considered. The directions of further research are determined. Ref. 42, fig. 5.

Intelligent Perception and Seam Tracking System for Thick Plate Weldments Based on Constant-Focus Optical Path

To achieve efficient and accurate thick plate welding, as well as to precisely extract and plan the paths of complex three-dimensional weld seams in large steel structures, this study introduces a novel vision-guided approach for robotic welding systems utilizing a constant-focus laser sensor. This methodology specifically targets and mitigates several critical shortcomings inherent in conventional vision-guided welding techniques, including limited detection ranges, diminished precision in both detection and tracking, and suboptimal real-time performance. For preprocessed weld images, an improved grayscale extreme centroid method was developed to extract the center of the light stripe. Furthermore, a sophisticated feature point extraction algorithm, which integrates a maximum distance search strategy with a least-squares fitting procedure, was developed to facilitate the precise and timely identification of weld seam characteristic points. To further optimize the outcomes, a cylindrical filtering mechanism was employed to eliminate substantial discrepancies, whereas local Non-Uniform Rational B-Spline (NURBS) curve interpolation was utilized for the generation of smooth and accurate trajectory plans. A spatial vector-based pose adjustment strategy was then implemented to provide robust guidance for the welding robot, ensuring the successful execution of the welding operations. The experimental results indicated that the proposed algorithm achieved a tracking error of 0.3197 mm for welding workpieces with a thickness of 60 mm, demonstrating the method’s substantial potential in the manufacturing sector, especially in the domain of automated welding.

PEMBERDAYAAN UKM INDUSTRI MANUFAKTUR DI RANDU, KECAMATAN KENJERAN KOTA SURABAYA

Recently, the industrial of manufacturing has grown into industry 4.0 and its progress significantly enhanced. The activity of public-serving is to develop the ability of small companies to manufacture. Regarding it, a semi-auto welding machine is required to revolute their performance in the small industry. Further, the welding knowledge obtained by training. That is, the public serving is at CV. Manshurin. The methods of public-serving aim to develop the small company. The first activity of it has done by upgrading the welding machine. Thus, training for employees to the welding characteristics is important. An invited trainer in a short class meeting is to deliver the information on the welding morphology and guide to operate the semi-automatic welding machine. Regarding it, the employee training has been done offline. the employee’s knowledge of the welding system increased. Further, the employee of CV. Manshurin skills are also increased. Therefore, they can operate a new welding machine (a semi-automatic welding machine). That is, those facts concluded that the employees receive the enhancement of knowledge, especially the morphology of the welding characteristic. In which, its formations are presented by a trainer who is invited to its training day. Thus, a semi-automatic welding machine improves the quality of the welding result.

Automated Weld Path Generation in Cluttered Environments Using Segmentation and Iterative Closest Point Workpiece Localization

Abstract A significant amount of manufacturing is performed by small to medium enterprises (SMEs), but these manufacturers often have lower adoption rates of automation. The cost and complexity associated with traditional robot systems slow the adoption of robotic welding operations for SMEs. The recent increase in collaborative robotic welding systems is bridging the gap, however, by reducing the complexity of installing, maintaining, and training operators to perform weld operations with collaborative robotics. These systems add flexibility in the range of operator use and ease of deployment. These systems however still rely on kinematic registration between the robot-mounted torch and workpiece on any open-loop weld. This requires precise placement of the workpiece prior to performing a weld. This work will discuss a method for part identification and registration in a welding task as a step toward automated weld path generation. The method is based on lower-resolution 3D cameras (RGBD cameras) using a combination of color and depth information. This information is used to both identify the workpiece within a workspace that may have other, non-workpiece items, and then provide registration or localization information of the workpiece within a resolution that could allow follow-on near-position strategies to achieve final weld path identification.

Passive vision based three-dimensional seam tracking using a stereo vision system with a single HDR camera

Seam tracking is a crucial feature that an automatic welding system must have. The laser tracking algorithm offers high accuracy but faces challenges in identifying seams with extremely narrow gaps, as the deformation of the laser stripe becomes difficult to detect in such cases. In contrast, the passive vision-based algorithm can effectively capture narrow gap information from the welding scene, making it more suitable for recognizing narrow seams. However, most of proposed passive vision-based seam tracking is based on “teaching and playback” mode and can only realize planar tracking. In medium and thick steel plate welding, the workpieces are so large that the “teaching and playback” based control algorithm is unsuitable. Therefore, in this paper, a stereo vision system with a single camera and the corresponding calibration algorithm are developed to achieve three dimensional seam tracking. Compared to stereo system with dual camera, the proposed system is cheaper and easier to synchronize acquisition. Moreover, to get out of the “teaching and playback” control strategy, a vector control algorithm without cumulative error is proposed. Results of nine experiments show that the average error of the proposed seam tracking system is less than 1.0662mm and the maximum error is 1.8030mm.

Research on automatic welding system for oil and gas pipeline based on laser tracking technology

Abstract With the growing energy demand both domestically and internationally, significant progress has been made in the construction of long-distance oil and gas pipelines and the maintenance of in-service pipelines, which has simultaneously raised higher requirements for automatic welding equipment, process methods, and efficiency. In recent years, automatic welding equipment used for oil and gas pipeline welding has predominantly employed arc-tracking technology, which meets the requirements for fully automatic fill and cap welding in standard groove configurations with stable welding quality. However, in hot-work welding processes for in-service pipeline maintenance and emergency repairs, manual alignment and cutting result in irregular weld seams, leading to poor performance of automatic welding equipment and, consequently, reliance on manual welding, which is inefficient. To address this, a specialized automatic welding machine with a laser vision weld seam tracking system was designed for welding irregular weld seams in long-distance oil and gas pipelines. Research was conducted on its mechanical system, control system, welding system, and tracking process. The specialized machine primarily consists of a power supply box, control box, industrial computer, laser sensing system, and welding carriage. During welding, the laser sensor measures three-dimensional information such as the seam size and center offset in real time along the direction of the welding carriage movement and feeds it back to the controller through the communication system of the machine. The main control system receives the information and adjusts the welding torch’s movement and welding process parameters through internal tracking control algorithms. Welding experiments were conducted on X80 steel V-groove welds of long-distance oil and gas pipelines. The results show that the welding machine can accurately identify the weld seam width, center offset, and height offset, and adjust the welding torch actions and parameters accordingly, achieving fully automated adaptive tracking welding. The precision of single torch oscillation tracking during welding can reach 0.5 mm, and the welding quality is good, meeting the requirements for single-layer single-pass fill welding, and multi-pass welding of irregular pipeline weld seams.

Microstructure and Mechanical Properties of a Weld Seam from Magnetron High-Current CO2 Welding

External magnetic field (EMF)-assisted high-current CO2 welding is beneficial for improving the large spatter and poor performance of the welding heat-affected zone for mild steels under high-current welding specifications. In this paper, the droplet transfer behaviors were determined using a high-speed camera on a self-developed magnetically controlled CO2 welding system. Based on these welding specifications, a three-dimensional, transient, multi-energy field coupling welding system model to investigate the mechanism of the droplet and molten pool in EMF-assisted welding was developed. The microstructure and mechanical properties of the welded joint were systematically studied. The results show that the Lorentz force applied by the EMF to twist the droplet decreases the accumulated energy in the short-circuited liquid bridge and changes the liquid metal flow condition, both of which reduce the spatter by 7% but increase the welded joint hardness by 10% and tensile strength by 8%.

Virtual numerical control: an approach towards autonomous manufacturing with a case study in welding

Today’s customer lifestyles have reshaped their expectations and preferences, driving a growing demand for tailor-made products. While current conventional manufacturing (MNF) systems are robust, they often lack the flexibility needed to accommodate customization. Most MNF systems, despite advances in technology and machinery, still rely on executing predefined instructions, limiting their flexibility. In contrast, human workers excel at handling product variations due to their cognitive abilities, which allow them to perceive, analyze, and make appropriate decisions to adapt to changing conditions. This study introduces virtual numerical control (VNC) as a solution to upgrade MNF systems and overcome these limitations. VNC aims to transform MNF systems into cognitive entities capable of autonomous decision-making, enabling greater flexibility to meet customization demands. To demonstrate the potential of VNC, we implemented it in a welding system as a practical case study. The results showed that VNC enabled the system to operate autonomously. It accurately identified the shape of the objects to be welded, determined the appropriate welding paths, and executed them with high precision, all without human intervention. This highlights the significant potential of VNC technology for broader applications in industrial automation in welding and beyond.

Influence of the Pulse Mode of Manual Metal Arc Welding on Weldment Distortions.

As a result of the thermo-mechanical impact during welding, distortions are generated in welded structures. These distortions significantly influence the geometric and dimensional accuracy of welded structures, in many cases lowering their working characteristics and reliability. An optimal design for welded structures is a prerequisite for increased reliability and reduction in manufacturing cost, and such an optimal design can be achieved knowing the distortions in weldments. Despite the fact that pulsed metal inert gas welding and metal active gas welding have been broadly applied in the last few decades, nowadays, few manufacturers, for instance, Fronius, EWM, Redco, and Perfect Power Welders, offer such an option for manual arc welding. This work aims to determine the influence of the parameters of pulsed welding modes on distortions that are generated during manual arc welding. Two different inverter welding power sources were used, and the welding distortions were measured by 3D scanning. The results showed that the pulsed mode during manual arc welding led to a reduction in distortions compared to the conventional welding mode. The crucial part of the manual welding system proved to be the qualification and performance of the welder.

Improved semantic segmentation method for weld penetration prediction of TIG welding with dual ellipsoid heat source

TIG welding is a manufacturing process that uses argon as a shielding gas and tungsten as an electrode to join metals at high temperatures. The weld penetration is the key to determining the quality of the weld. However, the lack of sensing technology makes weld penetration difficult to predict, which imposes a major challenge to process stability and weld quality. To address this challenge, a semantic segmentation-based approach for calibrating the weld penetration prediction model under dual ellipsoidal heat source is proposed to improve the prediction accuracy. To realize this, a semantic segmentation model Self-Attention-Structural-Reparameterization-BiSeNet (SASR-BiSeNet) is built for molten pool parameter extraction. The model introduces a self-attention mechanism as an enhancement to the convolution module. Meanwhile, the RepVGG-style structural reparameterization design decouples the training-time and inference-time architectures. Further, a mask feature extraction method is designed to obtain the calibration parameters of the molten pool and to correct the prediction model. The accuracy of the calibrated prediction model is verified by welding experiments using 304L steel materials on a robotic welding system. The results show that the maximum Mean Intersection over Union (mIoU) of the SASR-BiSeNet is 92.51 %, which is a 13.87 % improvement compared to the BiSeNet, and the maximum depth of molten pool error decreasing from 16.59 % to 9.84 %. This method can improve the precision of welding penetration control and plays an important role in promoting welding intelligence.

Multi-Station Multi-Robot Welding System Planning and Scheduling Based on STNSGA-D: An Industrial Case Study

Multi-Station Multi-Robot Welding System Planning and Scheduling Based on STNSGA-D: An Industrial Case Study

Selection of optimal polymer joining technology: Insights and decision support through interrelated case studies using CARCACS method

Polymer materials play an essential role in the automotive, aerospace, packaging, and healthcare industries, necessitating reliable joining processes to ensure structural integrity, functionality, and cost efficiency. Choosing the optimal polymer joining technology involves evaluating various criteria, such as design freedom, investment, joint quality, process adaptability, cycle time, etc., for prioritization and informed decision-making. This study aims to systematically assess polymer joining processes to improve efficiency and sustainability in industrial applications. Two interrelated case studies are conducted using the CARCACS (“Criteria-wise Alternative Ranking and Correlation Analysis for Composite Scoring”) method. The first case study identifies laser transmission welding as the most suitable joining process among eight commonly used processes based on multiple evaluation criteria. The second case study refines this selection by examining various laser welding systems, with fibre lasers emerging as the optimal choice. Validation through comparison with other MCDM (Multi-Criteria Decision-Making) methods and Spearman's rank correlation coefficients reveals strong agreement and robust decision-making. Sensitivity analysis further confirms the stability of the top-ranked alternatives across different scenarios. This research provides a robust framework for selecting polymer joining technologies and demonstrates the practical implications for optimizing these technologies in industrial applications.

Weld seam object detection system based on the fusion of 2D images and 3D point clouds using interpretable neural networks

This study introduces a novel approach that addresses the limitations of existing methods by integrating 2D image processing with 3D point cloud analysis, enhanced by interpretable neural networks. Unlike traditional methods that rely on either 2D or 3D data alone, our approach leverages the complementary strengths of both data types to improve detection accuracy in environments adversely affected by welding spatter and smoke. Our system employs an improved Faster R-CNN model with a ResNet50 backbone for 2D image analysis, coupled with an innovative orthogonal plane intersection line extraction algorithm for 3D point cloud processing. By incorporating explainable components such as visualizable feature maps and a transparent region proposal network, we address the “black box” issue common in deep learning models.This architecture enables a more transparent decision-making process, providing technicians with necessary insights to understand and trust the system’s outputs. The Faster-RCNN structure is designed to break down the object detection process into distinct, understandable steps, from initial feature extraction to final bounding box refinement. This fusion of 2D-3D data analysis and interpretability not only improves detection performance but also sets a new standard for transparency and reliability in automated welding systems, facilitating wider adoption in industrial applications.

Derivation of Analytical Expressions for Fast Calculation of Resistance Spot Welding System Currents

Derivation of Analytical Expressions for Fast Calculation of Resistance Spot Welding System Currents

Hybrid use of a robotic welding system in remote laser separation of thin-sheet Al casings for the recycling of battery packs

Hybrid use of a robotic welding system in remote laser separation of thin-sheet Al casings for the recycling of battery packs

Welded Gold Nanoparticle Assemblies Defined Plasmonic Coupling.

Nanoparticle assemblies with interparticle ohmic contacts are crucial for nanodevice fabrication. Despite tremendous progress in DNA-programmable nanoparticle assemblies, seamlessly welding discrete components into welded continuous three-dimensional (3D) configurations remains challenging. Here, we introduce a single-stranded DNA-encoded strategy to customize welded metal nanostructures with tunable morphologies and plasmonic properties. We demonstrate the precise welding of gold nanoparticle assemblies into continuous metal nanostructures with interparticle ohmic contacts through chemical welding in solution. We find that the welded gold nanoparticle assemblies show a consistent morphology with welded efficiency over 90%, such as the rod-like, triangular, and tetrahedral metal nanostructures. Next, we show the versatility of this strategy by welding gold nanoparticle assemblies of varied sizes and shapes. Furthermore, the experiment and simulation show that the welded gold nanoparticle assemblies exhibit defined plasmonic coupling. This single-stranded DNA encoded welding system may provide a new route for accurately building functional plasmonic nanomaterials and devices.

Physical simulation and computational modelling for validation of soft magnetic composite impeder performance

Induction tube welding systems utilize an internal magnetic flux controller (impeder) to improve process efficiency. Work has previously been done showing that soft magnetic composite (SMC) materials may be suitable to improve these systems. A test stand was devised for the physical simulation of SMC impeder performance for use in induction tube welding systems. Tests were run to determine the loading and cooling conditions in which an impeder core made of SMCs could survive. Additionally, 2D thermal simulations were run to determine the cooling system thresholds given a particular magnetic loading of the core. The goal of these tests was to expand the design envelopes in which impeder cores made of SMCs could survive and validate their use in induction tube welding systems.

Strain-based multi-dimensional force sensing system for robotic friction stir welding

Accurately measuring the force in friction stir welding (FSW) is essential for monitoring and controlling the welding process. However, current research primarily focuses on force sensing in gantry FSW equipment, which has limited demand compared to FSW robot. Commercial force sensors are mostly designed for six-axis welding robot and lack for high-force hybrid FSW robot. To address this gap, we developed a wireless multi-dimensional force sensing system for hybrid FSW robot. Our system utilizes elastomer and incorporates 8 pairs of strain gauges to detect tiny deformations. Through calibration, we achieved a wider measurement range than most commercial sensors, ensuring high accuracy with low cross-talk. Extensive testing determined the static and dynamic characteristics of the system. We performed robotic FSW experiments, analysing the force/torque characteristics in each direction and investigating the effects of welding speed and plunge depth on axial force. The results demonstrate the stability and practicality of our system.

Wire-feeding friction stir welding for large-gap width tolerances

A novel method, named wire-feeding friction stir welding, was proposed for welding large-gap-width joints. Continuous wire feeding and welding systems were designed. AA6082-T6 aluminium alloy plates with a gap width of 2 mm were welded using Al–Si alloy wires as the filler materials. Sound joints were obtained even if the gap width reached over 2/3 thickness of the base materials. Fine microstructures were obtained via dynamic recrystallisation induced by severe plastic deformation. The ultimate tensile strength of the joints reached 253.4 ± 1.3 MPa. The adaptability to working conditions of friction stir welding was improved for long welds of high-speed railway, ship and aircraft.

Application of ultrasonic vibration in magnesium alloy lap welding

In order to enhance the performance of magnesium alloy and galvanized steel welds, ultrasonic vibration was applied to the laser welding process, and the effect of ultrasonic on mechanical properties was verified through experimental methods. The laser welding system for the lap weld seam was designed, and the ultrasonic vibration module and image detection module were added, which can obtain the influence of ultrasonic vibration on the molten pool area. Under the conditions of ultrasonic vibration power of 1000 W and 0 W, the characteristics of the weld pool area, metallographic structure, tensile strength, fracture morphology, hardness, residual stress, wear resistance, and corrosion resistance of the weld specimen were compared. The image data acquisition structure indicated that ultrasonic vibration can effectively reduce the ineffective area of the molten pool and make the energy in the molten pool more concentrated. Under the influence of ultrasonic vibration, the maximum molten pool area decreased to 5.38 mm2, with a variation range of 3.9 %, and the proportion of pores was greatly reduced. Research found that ultrasonic vibration can significantly improve the microstructure characteristics of the fusion welding zone, with an average grain size reduced to 23 μm. The reduction of grain size and refinement of microstructure were beneficial to the improvement of mechanical properties of magnesium alloy joints, with a yield strength increase of 6.5 %. Ultrasonic vibration had little effect on the hardness of the heat affected zone, it can increase the average hardness of the weld zone by more than 5 % and reduce the maximum residual stress by more than 50 %. Under different pressure and friction speed conditions, the maximum wear amount can be reduced by more than 25 %. At the same time, the resistance to oxidation corrosion and electrochemical corrosion also can be improved to a certain extent.