Search Results (401)

As global energy demand continues to grow, the inherent safety requirements for natural gas long-distance pipelines are becoming increasingly stringent. Therefore, accurately analyzing the trends in pipeline defects using multi-round internal inspection data is of great significance for enhancing pipeline inherent safety levels and reducing the risk of pipeline medium leakage. However, existing pipeline in-line inspection data alignment methods for long-distance multi-round pipeline data alignment suffer from cumbersome alignment procedures and low computational efficiency. This paper proposes an adaptive threshold dynamic time warping defect alignment method (Adaptive Dynamic Threshold-Dynamic Time Warping, ADTH-DTW) for rapidly matching multi-round in-line inspection data. A new multi-round in-line inspection data alignment framework based on valve-weld-defect is established. By integrating the DTW algorithm into each alignment stage, unnecessary manual effort is avoided, significantly improving data alignment efficiency. First, the ADTH method is used to clean redundant weld seam data in the in-line inspection data. By dynamically generating expected values and combining an intelligent point selection strategy, the method accurately identifies and removes interfering data. Additionally, valve chamber data is used to correct the overall mileage, providing a data foundation for subsequent defect alignment. Second, the dynamic time warping algorithm is used to align weld seam data and establish a data mapping table. Finally, relative displacement methods are employed to achieve defect matching. The validation results from three rounds of in-vehicle inspection data tested on-site indicate that the ADTH-DTW algorithm achieves an average 23.08% improvement in alignment accuracy compared to methods such as DTW, KL divergence, JS divergence, and linear interpolation, with computational efficiency nearly tripled. This effectively addresses the issue of incompatible computational efficiency and accuracy in existing data alignment algorithms, thereby enhancing the intrinsic safety level of natural gas long-distance pipelines. Full article

To precisely evaluate the fatigue hot-spot stress concentration factor (SCF) of welded tubular joints and verify the accuracy of existing methods, this research selects Y-type tubular joints as the research subject. The dihedral angle formula is re-derived, and the dihedral angles corresponding to each polar angle along the intersection line are calculated using MATLAB R2018a (MathWorks Inc., Natick, MA, USA). After determining the geometric parameters of the weld profile in accordance with AWS specifications, finite element models named “AWS-max” and “AWS-min” are established in ANSYS 2022 R1 (ANSYS Inc., Canonsburg, PA, USA). These models meet the maximum and minimum allowable weld sizes respectively, and a novel modeling approach is proposed. Tests on tubular joints under axial tension loading are conducted, and the SCF is obtained through the surface stress interpolation method. Comparative analyses are carried out among the SCF from the established “AWS-max” and “AWS-min” weld models, the non-weld model, and the test results of the tubular joints. The results indicate that the weld geometric size has a significant impact on SCF: a larger weld cross-section results in a lower SCF. For the AWS maximum weld model, the SCF of the chord ranges from 4.21 to 5.42, and that of the brace ranges from 1.71 to 5.33; for the AWS minimum weld model, the chord SCF is 4.41–5.73, and the brace SCF is 2.11–5.79. The numerical results are in good accordance with the experimental data, while the non-weld model produces obviously conservative results with inconsistent distribution laws. The calculated dihedral angles obtained by the proposed method are highly consistent with the AWS standard. The modeling method is characterized by reliable accuracy and strong engineering applicability, and can be extended to the SCF calculation and fatigue evaluation of various tubular joints. Full article

This study evaluates the effectiveness of reinforcement measures for a corrugated steel pipe arch bridge subjected to differential settlement induced by underground mining. Using a ten-span continuous corrugated steel pipe arch bridge in Shandong Province as the engineering background, a refined finite element model was developed based on 12 months of in situ settlement monitoring data. The mechanical performance of three reinforcement schemes–inner lining concrete, inner lining concrete with nested steel pipes, and laterally welded steel plates–was systematically compared. The results indicate that under differential settlement, the maximum stress of the unreinforced structure reaches 75.74 MPa, primarily concentrated at the arch foot. Reinforcement with an inner concrete lining significantly improves structural performance; in particular, the 200 mm-thick lining reduces the maximum steel pipe stress by 61.8%, achieves a maximum reduction of 22.1% in crown displacement and approximately 11.2% in sidewall displacement, and limits the circumferential displacement amplitude to 12–17 mm, representing a reduction of 11.7–15%. The nested steel pipe scheme delivers reinforcement effects comparable to the pure inner lining concrete scheme, with a maximum crown displacement reduction of approximately 17.3%, though its overall additional advantages remain limited. In contrast, the laterally welded steel plate scheme reduces the maximum structural stress by 28.3%. While it exhibits favorable control over local displacements, its overall reinforcement effectiveness is inferior to that of the inner lining concrete scheme. These findings provide a useful reference for the reinforcement design and engineering application of corrugated steel pipe arch bridges in mining-induced subsidence areas. Full article

In the fabrication process of pipelines for petrochemical and other industries, weld reinforcement is often excessive and adversely affects subsequent processes such as anticorrosion treatment and surface coating. Weld reinforcement must be removed through a grinding process. Welding deformation and fit-up errors often lead to highly irregular weld geometries, which makes robotic grinding difficult and causes the task to still heavily rely on manual operation. To address this issue, this study proposes an automatic weld recognition and grinding trajectory planning method based on 3D visualization and deep learning. A weld recognition network, termed WSR-Net, has been developed based on an improved PointNet++ architecture with a cross-attention mechanism, achieving a segmentation accuracy of 98.87% and a mean intersection over union of 90.71% on the test set. An intrinsic shape signature (ISS) key point selection algorithm with orthogonal slicing-based pruning optimization is developed to robustly extract key weld ridge points that characterize the weld trend on rugged weld surfaces. According to the height differences between the weld and the adjacent base metal surfaces, the grinding reference surface is fitted using the weld contour through the moving least-squares method. The ridge line points are projected onto the grinding reference surface along the local normal to generate the expected grinding trajectory points. The grinding trajectory that meets the process constraints is generated through reverse layer slicing. Grinding experiments demonstrate that the proposed WSR-Net achieves robust segmentation performance for both planar and curved surface welds. With the reverse layered trajectory planning method, the proposed method enables high-precision automatic grinding of complex spatially curved surface welds. The results show that the final grinding mean error is 0.316 mm, which satisfies the preprocessing requirements for subsequent processes. The proposed method provides a feasible technical method for the intelligent grinding of spatially curved surface welds. Full article

Robotic pipe welding represents a key and rapidly evolving technology for the automation of pipe and pipe-joint welding processes with standard, intersecting, and complex geometries. This review analyses 84 studies published over the past three decades, categorising them into four primary research areas: general pipe welding, intersecting pipes, boiler and tube-to-tubesheet welding, and control and modelling. Two separate comparative analyses were conducted: one within intersecting pipe research and another within the control and modelling category. The aggregated findings reveal consistent, complementary patterns: simulation and laboratory experiments clearly dominate validation methods, while industrial-scale evaluations remain scarce. The results further demonstrate that control strategies, sensor integration, and validation levels are strongly interconnected, collectively determining system performance, reliability, and practical applicability. Despite significant progress, challenges remain, including system integration complexity, limited robustness in variable industrial environments, insufficient real-time adaptive control, and inconsistent quantitative performance evaluation. Further research should prioritise the development of digital twins, human–robot collaboration, multi-sensor fusion, reinforcement learning-based adaptive control, and scalable industrial deployment. This review provides an overview of current progress and outlines key directions for developing intelligent and reliable robotic pipe welding systems. Full article

Shop-floor weld inspection may appear to be a solved problem until a camera is deployed near a galvanized-sheet MIG welding line. The seam reflects light, the texture changes from frame to frame, and the defects of interest are often small and visually subtle. Additionally, the hardware near the line is rarely a data-center GPU. With those constraints in mind, this paper presents YOLO-MIG, a compact detector built on YOLOv10n for weld-seam inspection in practical production conditions. We make three focused changes to the baseline: a C2f-EMSCP backbone block to better preserve weak defect cues with modest parameter growth, a BiFPN neck to keep small-target information alive during feature fusion, and a C2fCIB head to clean up predictions that otherwise get distracted by seam edges and illumination artifacts. On a workshop-collected dataset containing 326 original images, with the training subset expanded through augmentation to 2608 labeled samples in total, YOLO-MIG achieves 98.4% mAP@0.5 and 56.29% mAP@0.5:0.95 on the test set while remaining lightweight (1.83 M parameters, 3.87 MB FP16 weights). Compared with YOLOv10n, the proposed model improves mAP@0.5 by 9.36 points and mAP@0.5:0.95 by 4.89 points, while reducing parameters, GFLOPs, and model size by 43.4%, 19.9%, and 29.9%, respectively. The results suggest that YOLO-MIG is not only accurate but also realistic to deploy at the edge for intelligent weld quality control. Full article

This paper examines the use of high-rigidity Tau-robots in friction stir welding, where process loads are very high. The rigidity of Tau-robots increases at the expense of the workspace. Therefore, the right configuration of the Tau-robot is sought to reconcile rigidity and workspace requirements. This is studied by use of kinematics, followed by static and modal analysis. In particular, by extending an existing kinematic model employing free vectors, the robot workspace was derived in non-dimensional parametric form and was then maximized through evolutionary optimization. However, finite element static and modal analysis that were carried out subsequently may prove, as in a case demonstrated here, that the optimized configuration may not withstand high loads, typically axial forces of 15 kN and torques of 80 Nm, and it may also be susceptible to forced vibrations in the typical spindle rotation range up to 3000 rpm. As a rectification measure, it was shown how a modified configuration by placing robot kinematic chain bases further apart and shortening robot links achieves higher rigidity, axial displacement being reduced by one or two orders of magnitude to below 1 mm and increases critical modal frequency 3 to 5 times depending on the workspace position, of course sacrificing part of the workspace, i.e., reducing it 3-fold to enclose welding lines in a rectangle of dimensions 700 × 800 mm. In the quest for the appropriate robot configuration desired dimensions of parts to be welded and available standard components are briefly considered, too. Full article

Aiming to solve the persistent problem of edge cracking in magnesium alloy cast-rolling, this numerical simulation study introduces an innovative magnetic field-assisted approach. Utilizing Lorentz force, the process dynamically transforms the solidification front morphology from an arc-shaped (“Ɔ”) to a linear (“1”) configuration. Simulation results reveal that, while magnetic field-induced thermal effects minimally impact the solidification front, the Lorentz force fundamentally alters the flow field dynamics. This modification yields a more uniform temperature distribution and reduces velocity gradients between the symmetric center and edge regions, thereby promoting the transition to a linear solidification front essential for synchronous solidification and deformation across the entire plate width. Furthermore, variations in magnetic field intensity and frequency critically influence vortex flow position and density within the cast-rolling zone. The optimization goal was to maximize the angle α between the side surface and solidification front, which characterizes the linearity of the front. With optimized parameters of 0.49 T magnetic field intensity and 8 Hz frequency, angle α reaches 65°. This marks a 62.5% increase compared to the conventional (non-magnetic) cast-rolling scenario and achieves a near-linear (“1”) solidification profile. Full article

This study examines the joining characteristics of Cu foil stacks to lead tabs using green-laser welding in the main-welding step of a sequential welding process for lithium-ion pouch cells. The influence of lap configuration, line and wobble seam strategies, and process parameters was systematically investigated in terms of bead morphology, mechanical performance, metallurgical characteristics, and electrical resistance. Under the present line-welding parameter window (2.0 kW, 100–200 mm/s), humping, pinholes, and porosity were observed, particularly in the upper lead-tab configuration, which is attributed to melt-pool/keyhole instability under the applied conditions. Wobble welding effectively suppressed these defects in the foil-stack configuration by promoting stable melt flow and efficient bubble expulsion. Mechanical tests revealed that the wobble-based seam strategy achieved a maximum tensile–shear load of approximately 1.28 kN at a wobble amplitude of 0.8 mm. Fracture analysis confirmed a transition from seam-type interfacial failure in line welding to ductile tearing in the heat-affected zone with wobble welding. In electrical performance, wobble welding reduced resistance to as low as 45 µΩ at a wobble amplitude of 1.2 mm, while line welding yielded higher and scattered values. These results should be interpreted as the combined outcome of the wobble-based seam strategy (beam oscillation together with overlapped stitch welding at a lower travel speed) under the present processing windows. A strictly matched A/B comparison at identical linear energy density and seam layout will be investigated in future work to isolate the effect of oscillation. Full article

To study the forming, microstructures, and mechanical properties of high-speed laser cladding thin-walled tube, 1Cr17Ni2 powder was used to perform high-speed laser cladding on a 1Cr17Ni5 stainless steel tube with a thickness of 1 mm. The effects of powder feeding rate, laser power, rotation speed, protective gas flow rate, powder defocusing amount, and powder feeding gas flow rate on the width, height, and penetration depth of the weld beads were investigated. Subsequently, the cladding of multi-pass was carried out, and the microstructures and microhardness of the cladding layer were studied. The results showed that laser power had the most significant effect on the width of the weld bead, and the width gradually increased with the increase in power. The powder feeding rate had the most significant effect on the height of the weld bead, and the height gradually increased with the increase in powder feeding speed. The powder feeding rate also had the most significant effect on the penetration depth, and the penetration depth gradually decreased with the increase in powder feeding speed. When multiple passes overlap, the microstructure of the cladding layer exhibits a distinct periodic distribution. Large-sized primary austenite columnar crystals exist in the cladding layer, and the main microstructure in the columnar crystals is martensite and possesses a small amount of residual austenite. The base material is composed of austenite and a small amount of martensite. The average microhardness of the substrate is 366 HV, and the microhardness of the cladding layer gradually decreases with increasing distance from the fusion line, from 562 HV to 532 HV. Due to the heat effect of the cladding on the substrate, the microhardness of the substance near the fusion line is only 239 HV. As the distance from the fusion line increases, the influence of heat effect decreases, and the microhardness gradually increases. Full article

Friction stir welding (FSW) of high-strength aluminum alloys, including EN AW 7020-T651, encounters significant challenges under weld line gap conditions, leading to compromised joint integrity. This study develops a predictive, data-driven framework to assess and optimize the gap bridgeability performance of FSW joints with weld line gaps ranging from 0 to 4 mm in 2 mm thick plates. A structured experimental matrix was implemented, systematically varying rotational speed, welding speed, axial force, and tool shoulder diameter. To promote stable material flow and consistent weld quality under varying gap conditions, a multi-pin tool was employed throughout the welding trials. This configuration supported defect-free weld formation across a broad process window and contributed to improved weld soundness under gap conditions. Weld quality was evaluated using a comprehensive, multi-criteria approach that required (i) defect-free joints verified by visual and cross-sectional (metallographic) inspection, (ii) an ultimate tensile strength of at least 230 MPa, and (iii) a novel metric termed weak area percentage (WAP). Derived from micro-hardness mapping, WAP quantified the proportion of the heat-affected zone (HAZ) exhibiting hardness below 96 HV, providing a more robust and spatially sensitive measure of mechanical integrity than conventional average hardness values. Two machine learning models, Logistic Regression and Random Forest, were trained to classify weld acceptability. The Random Forest model demonstrated superior performance, achieving 92.5% classification accuracy and an F1-score of 0.90. Feature importance analysis identified the interaction terms “welding speed × gap size” and “rotational speed × gap size” as the most influential predictors of weld quality. Full article

Reliable joining of multi-layer aluminum foil current collectors is crucial for enhancing the performance and safety of high-capacity lithium-ion batteries. However, laser welding of such thin-thick aluminum combinations is often hindered by porosity, cracks and unstable weld-pool behavior. In this study, a ring-mode fiber laser combined with sinusoidal oscillation and linearly gradient power modulation was employed to achieve high-quality lap welding between 80 layers of 1060 aluminum foil (1 mm in total thickness) and a 1.5 mm thick aluminum plate. Welding experiments and thermo-mechanical simulations were conducted to investigate the effects of welding speed (15–45 mm/s) and central-power modulation parameters (−2, 0, +2, +4) on weld morphology, defect formation, and mechanical properties. The results indicate that increasing the welding speed can effectively suppress cracks and improve the shear strength from 249.8 N to 403.9 N, but it also leads to an increase in porosity from 5.78% to 12.26% and deterioration of the weld reinforcement. Higher central-power modulation (+2, +4) transformed the weld-pool geometry from an ω shape to U shape, effectively suppressing fusion-line cracks but leading to increased porosity (up to 8.41%) and deteriorated surface morphology. Overall, a low welding speed of 15 mm/s combined with an optimized power modulation strategy achieves effective crack suppression while maintaining controlled porosity, resulting in a welded joint with superior comprehensive performance. This research provides a robust process solution for high-quality laser welding of multi-layer aluminum foil current collectors in power battery manufacturing. Full article

Friction stir spot welding (FSSW) is a novel variant of Friction Stir welding (FSW), developed by Mazda Motors and Kawasaki Heavy Industries to join similar and dissimilar materials in a solid state. It is an economic and environmentally friendly alternative to resistance spot welding (RSW). The FSSW technique, however, includes some structural defects imbedded within the weld joint, such as keyhole formation, hook crack, and bond line oxidation challenging the joint strength. The unique properties of nanomaterials in the reinforcement of metal matrices motivated researchers to enhance the FSSW joints’ strength. Previous studies successfully fabricated nano-reinforced FSSW joints. At different volumetric ratios of nano-reinforcement, nanoparticles may agglomerate due to inefficient stirring of the welding tool pin, forming stress concentration sites and brittle phases, affecting tensile and fatigue strength under static and cyclic loading conditions, respectively. This work investigated how the welding tool pin affects stirring efficiency by controlling the distribution of a nano-reinforcing material within the joint stir zone (SZ), and thus the tensile and fatigue strength of the FSSW joints. Sheets of AA6061-T6 of 1.8 mm thickness were used as a base material. In addition, graphene nanoplatelets (GNPs) with lateral sizes of 1–10 µm and thicknesses of 3–9 nm were used as nano-reinforcements. GNP-reinforced FSSW specimens were prepared and successfully fabricated. Optical microscope (OM) and field emission scanning electron microscope (FE-SEM) methods were employed to visualize the GNPs’ incorporation into the SZs of the FSSW joints. Micrographs of as-welded specimens showed lower formations of scattered, clustered GNPs achieved by the threaded pin tool compared to continuous agglomerations observed when the cylindrical pin tool was used. Tensile test results revealed a significant improvement of about 30% exhibited by the threaded pin tool compared to the cylindrical pin tool, while fatigue test showed an improvement of 46–24% for the low- and high-cycle fatigue, respectively. Full article

Faced with the contradiction between the increasingly growing demand and labor-intensive manufacturing modes, in the current era of rapid development of informatization and artificial intelligence, improving manufacturing efficiency by means of automated manufacturing equipment has become a recognized development direction for most shipyards. This trend is particularly evident in the manufacturing of sub-assemblies, which are the smallest composite units of the hull. Taking an automated sub-assembly welding line in a shipyard as the research object, this paper constructs a mathematical model aimed at optimizing production efficiency based on the analysis of its operational processes and characteristics and proposes an improved two-layer fruit fly optimization algorithm (ITLFOA) for solving the automated sub-assembly welding line scheduling problem (ASWLSP). The proposed ITLFOA features a two-layer nested algorithm structure, with several key improvements proposed for both optimization layers, such as heuristic rules for spatial layout, improved neighborhood operators, an added disturbance mechanism, and an added population diversity restoration mechanism. Finally, the performance of ITLFOA is validated through a comparative analysis against the initial two-layer fruit fly optimization algorithm (initial TLFOA), the well-established Variable Neighborhood Search (VNS) algorithm and the actual manual operation results on a specific case of a shipyard. Full article

Empirical approaches alone have significant limitations for accurate estimation of the fracture toughness of welds in gas line pipes being considered for repurposing to hydrogen service. These problems arise because most samples machined from ex-service welds contain a range of microstructures. The different microstructural zones have different properties and even when compact tension samples with side grooves are utilized, it is unlikely that plane strain conditions are achieved during laboratory testing. Thus, the measured toughness may not be directly relevant to assessing in-service performance. The present research has been undertaken as part of an integrated series of projects seeking to define a robust protocol for assessing the damage tolerance of piping used for the transmission of hydrogen, especially when considering repurposing existing infrastructure. The key work described in this paper involved establishing heat treatments which produced microstructures relevant to the constituents found in ex-service welds of X46 type steel. Following comprehensive microstructural characterization, these heat treatments were applied to steel sections which allowed for the fabrication of standard compact tension specimens, which were subsequently tested in hydrogen to measure fracture toughness. The results obtained showed that the fracture behavior varied for different microstructures. To identify the influence that hydrogen gas has on the performance of pipeline steels, it is important to assess microstructures relevant to the welds present, as testing only on base metal may not provide conservative information. However, the results from well-planned and carefully executed programs can be used to identify the relative performance in hydrogen. The data can also be used as critical input to models which form part of an integrated approach to structural integrity assessment. Full article