Weld Surface Research Articles

Investigation into welding residual stress of high-performance-steel Q500qE welded-joint

This study investigates the welding residual stress (WRS) spatial distribution in a high-performance steel (HPS) Q500qE unequal-thickness butt-welded joint of steel bridge tower. The hole-drilling and contour methods were used to measure the initial residual stress (IRS) of the base material and WRS in the welded joint. Additionally, the welding process was simulated using ABAQUS, incorporating IRS of base material to study WRS of welded joint. The comparison between measured and simulated WRS showed good agreement, validating the simulation's effectiveness and accuracy. The results reveal that simulated longitudinal and transverse WRSs (LWRS and TWRS) on the top and bottom surfaces indicate high tensile stresses in the weld region, exceeding the measured yield strength of the Q500qE steel. These stresses decrease and transition to compressive states as the distance from the weld increases. LWRS contours show a high tensile stress region along the plate thickness in the weld. Away from the weld, the LWRS is compressive at the surface layer and tensile in the interior zone, especially in the 56 mm-thick base material. The simulated TWRS shows high tensile stress primarily at the weld surface layer, with compressive stress mainly in the surface layer of the 56 mm-thick base material. Compared to vertical WRS (VWRS), the simulated LWRS and TWRS with IRS show higher stress levels and significant stress gradients.

Optimization of bobbin tool friction stir welding parameters of AZ31 magnesium alloy based on FEM and its influence mechanism on mechanical properties

Based on the 3D transient heat transfer theory, the finite element model of bobbin tool friction stir welding (BT-FSW) of AZ31 magnesium alloy sheet is established. The effects of different process parameters on the quality of BT-FSW joint of magnesium alloy were discussed using temperature distribution, mechanical properties, fracture morphology analysis, and EDS element distribution analysis. The results show that in the process of BT-FSW, the cross-section temperature of the plate is symmetrically distributed in an hourglass shape, the AS is slightly lower than that of RS, and the transverse temperature is distributed in an ‘M’ shape. When the rotating speed is 700 rpm and the welding speed is 180 mm/min, the weld surface is smooth, and its ultimate tensile strength can reach 81.82% of the base metal strength. The tensile specimen is quasi-cleavage fracture. When the heat input is insufficient, there are a lot of Al8Mn5 Precipitated phases in the TMAZ fracture zone, which increases the fracture brittleness of the joint. When the heat input is enough, the precipitated phase dissolves evenly, the river-like fracture surface of the joint retains the dimple characteristics, and the mechanical properties are improved.

Explaining the Anomaly Detection in Additive Manufacturing via Boosting Models and Frequency Analysis

Anomaly detection is an important feature in modern additive manufacturing (AM) systems to ensure quality of the produced components. Although this topic is well discussed in the literature, current methods rely on black-box approaches, limiting our understanding of why anomalies occur, making complex the root cause identification and the consequent decision support about the action to take to mitigate them. This work addresses these limitations by proposing a structured workflow designed to enhance the explainability of anomaly detection models. Using the wire arc additive manufacturing (WAAM) process as a case study, we examined 14 wall structures printed with INVAR36 alloy under varying process parameters, producing both defect-free and defective parts. These parts were classified based on surface appearance and welding camera images. We collected welding current and voltage data at a 5 kHz sampling rate and extracted features from both time and frequency domains using a knowledge-based approach. Isolation Forest, k-Nearest Neighbor, Artificial Neural Network, XGBoost, and LGBM models were trained on these features, and the results shown best performance of boosting models, achieving F1 scores of 0.927 and 0.945, respectively. These models presented higher performance compared to other models like k-Nearest Neighbor, whereas Isolation Forest and Artificial Neural Network posses lower performance due to overfitting, with an F1 score of 0.507 and 0.56, respectively. Then, by leveraging the feature importance capabilities of these models, we identified key signal characteristics that distinguish between normal and anomalous behavior, improving the explainability of the detection process and in general about the process physics.

Workpiece temperature control in friction stir welding of Inconel 718 through integrated numerical analysis and process control

Friction stir welding (FSW) offers significant advantages over fusion welding, particularly for high-strength alloys like Inconel 718. However, achieving optimal surface quality in Inconel 718 FSW remains challenging due to its sensitivity to temperature fluctuations during welding. This study integrates finite element simulations, statistical analysis, and advanced control methodologies to enhance weld surface quality through adequate thermal management. High-fidelity simulations of the FSW process were conducted using a validated 3D transient COMSOL Multiphysics model, producing a comprehensive dataset correlating process parameters (rotational speed, axial force, and welding speed) with workpiece temperature. This dataset facilitated statistical analysis and parameter optimization through Analysis of variance (ANOVA) method, leading to a deeper understanding of process variables. A nonlinear state-space system model was subsequently developed using experimental data and the system identification toolbox in Matlab, incorporating domain-specific insights. This model was rigorously validated with an independent dataset to ensure predictive accuracy. Utilizing the validated model, tailored control strategies, including proportional-integral-derivative (PID) and model predictive control (MPC) in both single and multivariable configurations, were designed and evaluated. These control strategies excelled in maintaining welding temperatures within optimal ranges, demonstrating robustness in response times and disturbance handling. This precision in thermal management is poised to significantly refine the FSW process, enhancing both surface integrity and microstructural uniformity. The strategic implementation of these controls is anticipated to substantially improve the quality and consistency of welding outcomes.

Corrosion fatigue crack propagation behaviour in different micro-regions of steel/aluminum laser-MIG hybrid fusion-brazed joints

Evaluating corrosion fatigue crack propagation (CFCP) behaviour in different micro-regions of steel/aluminium welded joints is crucial for ensuring the safety and reliability of these joints in service environments. However, the CFCP behaviour of steel/aluminum welded joints has rarely been studied. This study explores the CFCP behaviour of steel/aluminium laser-metal inert gas hybrid fusion-brazed joints in different micro-regions under a simulated corrosive environment (3.5 wt% NaCl solution) at room temperature. A self-made 5 KN electronic servo testing machine was used to apply a sinusoidal wave load (stress ratio R = 0.1, frequency = 0.5 Hz) to single-edge notched tensile specimens. The notches were located at the weld, heat-affected zone (HAZ) and steel/aluminium interface (abbreviated as interface). The fatigue crack propagation rate (da/dN) of different micro-regions in steel/aluminium welded joints followed the order of interface > weld > HAZ under corrosive environment and air conditions. Compared with air, the corrosive environment triggered a markedly higher da/dN, irrespective of notch location at the weld, HAZ or interface. This accelerated da/dN resulted from the combined effects of anodic dissolution, chloride ions and galvanic corrosion. The electron backscatter diffraction results indicated that compared with the weld and HAZ specimens, the HAZ specimen exhibited lower da/dN, attributed to its small grains, higher proportion of high-angle grain boundaries and increased geometrically necessary dislocation density. Fatigue striations were clearly observed on the weld and HAZ fracture surfaces, while a brittle fracture pattern was observed on the corrosion fatigue fracture surface for the interface.

Intelligent Grinding System for Medium/Thick Plate Welding Seams in Construction Machinery Using 3D Laser Measurement and Deep Learning

With the rapid development of the construction machinery industry, thick plate welds are increasingly needing efficient, accurate, and intelligent processing. This study proposes an intelligent grinding system using 3D line laser measurement and deep learning algorithms to solve the problems of inefficiency and inaccuracy existing in traditional weld grinding methods. This study makes use of 3D line laser measurement technology and deep learning algorithms in tandem, which perform automated 3D measurement and analysis to extract key parameters of the weld seam, in conjunction with deep learning algorithms applied on image data of the weld seam for the automatic classification, positioning, and segmentation of the weld seam. The entire work is divided into the following: image acquisition, motion control, and image processing. Based on various weld seam detection algorithms, the selected model was MNet-based DeepLab-V3. An intelligent trimming system for welding seams based on deep learning was constructed. Experiments were conducted to verify the feasibility and accuracy of the 3D line laser measurement technology for weld seam inspections, and that the deep learning algorithm can effectively identify the type and location of the weld seam, thus predicting the trimming strategy. With an accuracy far superior to conventionally based methods in accurate detection and regrinding of weld surface defects, the system proves advantageous for improved weld regrinding productivity and quality. It was determined that the system presents significant advantages in reinforcing weld regrinding when it comes to efficiency and quality, thus initiating a paradigm of using intelligent treatments for medium/thick plate welds in the construction machinery industry.

Segmentation-assisted classification model with convolutional neural network for weld defect detection

Detecting weld defects in battery trays is crucial for the safety of new energy vehicles. Existing methods for weld surface defect detection, relying on traditional computer vision algorithms and convolutional neural networks with substantial image-level labeled data, face challenges in accurately identifying small defects, especially with limited samples. To address these issues, we developed an innovative Segmentation-Assisted Classification with Convolutional Neural Networks (SACNN) model. SACNN integrates a common feature extraction subnet, a segmentation subnet enhanced by a multi-scale feature fusion module, and a classification subnet specifically designed for precise defect detection. A joint loss function co-trains the segmentation and classification subnets using both image-level and pixel-level labels, enhancing the model’s ability to accurately detect small defect regions. Our model demonstrates notable improvement, achieving accuracy gains ranging from 2% to 18% compared to existing state-of-the-art methods, with an overall accuracy of 94.09% on an industrial dataset of battery tray welds. To further evaluate the generalization capability of our model, we evaluated it on the publicly available Magnetic Tile dataset, achieving state-of-the-art results in this challenging context. Additionally, we conducted comprehensive ablation studies to validate the contribution of each component in our approach and utilized visualization techniques to enhance the interpretability of our model. These advancements represent a significant contribution to the state of the art in aluminum alloy weld defect detection.

Study on fracture behaviour of pipeline girth welds based on curved wide plate specimens: Experimental and numerical analysis

Understanding the fracture characteristics and strain capacity of pipelines with girth welds under external loads is crucial for evaluating pipeline safety. The use of curved wide plate (CWP) specimens closely resembling full-scale (FS) pipelines in geometry provides a more realistic representation of crack tip constraint states compared to small-size fracture toughness test specimens in laboratory settings. This study aims to investigate the ductile fracture characteristics of center cracks on the outer surface of girth welds in high-grade steel pipelines under external loads through large-scale CWP tensile tests and advanced numerical simulations. Tensile tests were conducted on CWP specimens using a kiloton tensile testing machine, with double crack opening displacement (COD) gauge monitoring crack mouth opening displacement (CMOD), and high-precision displacement sensors and strain gauges tracking deformation and strains at various positions. The study yielded significant experimental results, and a finite element (FE) model of the CWP was developed using the nonlinear finite element method (FEM) to validate the experimental data against simulation results. The FE model was then used to investigate the influence of material properties on crack propagation resistance and driving force curves. A method for determining the ultimate tensile strain capacity (UTSC) of pipelines based on actual material fracture toughness was proposed. This research contributes valuable experimental data for further exploration of fracture behaviour in large-scale pipeline girth welds and offers insights for safety evaluations of such welds.

Study on microstructure and corrosion behavior of T-joints of 2A12 and 2A97 aluminum alloys by FSW

T-shaped joints of high-strength aluminum alloy welded by friction stir welding (FSW) are expected to replace the traditional riveting structures. However, the popularization of FSW in aerospace industry is still hindered the corrosion of T-joint. Herein, T-joints of 2A12 and 2A97 aluminum alloys are prepared and studied via structural characterization and corrosion tests. The microstructures and constituents of different micro zones in T-joints before and after corrosion tests are characterized and analyzed particularly. The internal relationship between different micro zones in T-joints and their corrosion behaviors are clarified, which provides theoretical basis for improving welding process and surface protection after welding.

Effects of laser non-uniform shock peening on the microstructure and fatigue performance of SUS 304 stainless steel welded joints

Residual tensile stresses and microstructural heterogeneity in welded joints are primary factors that degrade fatigue performance. As an effective post-weld strengthening method, Laser Shock Peening (LSP) can address these issues. Given the personalized demands of different regions, this paper proposes a Laser Non-Uniform Shock Peening (LNUSP) technique. This approach involves applying high pulse energy to the weld zone (WZ) and heat-affected zone (HAZ), and low pulse energy to the base material (BM) to achieve a more uniform residual compressive stress distribution and refined microstructure, thereby improving overall performance and service life. Results indicate that LSP transforms residual tensile stresses on the weld surface into compressive stresses. Compared to original samples, uniformly LSP-treated samples, and locally LSP-treated samples, LNUSP-treated samples exhibit more uniform residual stress and hardness distribution. LSP significantly increases surface hardness, with LNUSP-treated samples achieving a maximum hardness of 308.3 HV. Additionally, LSP induces martensitic transformation in the BM and WZ areas, alters grain orientation, and promotes dislocation movement, resulting in dislocation tangling, dislocation networks, and twin structures, which refine grain size. Consequently, LSP markedly improves joint fatigue performance, delaying fatigue crack propagation. The fatigue life of LNUSP-treated samples is increased by 25.41 % compared to original samples, reaching levels comparable to high-energy large-area impacts. This enhancement is attributed to the uniform residual stress and refined grain structure.

Effect of oscillation parameters on weld surface morphology during laser beam oscillation welding of stainless steel

During laser beam oscillation welding (LBOW), the weld surface morphology is important because it influences the appearance of the workpiece and reflects the welding quality, and the oscillation parameters have an important effect on the weld surface morphology. Therefore, a combination of experimental research and numerical simulation is conducted to investigate the influence of oscillation parameters, including oscillation mode, oscillation frequency, and oscillation amplitude, on the weld surface morphology during LBOW. The calculation encompasses the oscillation trajectory, combined velocity, and energy distribution on the weld surface, varying with different oscillation parameters. A three-dimensional heat transfer and fluid flow model with the oscillation heat source is established to simulate the temperature and fluid flow behavior inside the weld pool. When the heat input is constant, an increase in oscillation frequency results in a decrease in weld width and a smoother surface. As the oscillation frequency increases, the weld width decreases, the surface becomes smooth, and the energy distribution on the weld surface becomes more uniform. The fact that the period of the surface pattern is almost equal to the oscillation period indicates a direct correlation between the formation of weld surface pattern and the oscillation trajectory in LBOW. Among all the oscillation modes, the minimum combined velocity which is equal to the welding velocity occurs at the inflection point in the linear oscillation mode, and the variation in combined velocity of the laser beam is the smallest for circular oscillation mode. The surface pattern is primarily influenced by the oscillation trajectory and fluid flow within the weld pool. Under conditions of lower oscillation frequencies or larger oscillation amplitudes, the fluid flow is weaker, and the surface pattern is primarily influenced by the oscillation trajectory. Conversely, when the fluid flow is stronger, the surface pattern is mainly determined by the fluid flow within the weld pool under conditions of higher oscillation frequencies or smaller oscillation amplitudes. This study explains the formation mechanisms of weld surface patterns and provides insights and guidance for selecting optimal oscillation parameters in LBOW.

The Influence of Variable Plasma Welding Parameters on Weld Geometry, Dilution Factor, and Microhardness

Weld surfacing is the process of applying a layer of metal to the surface of metal objects by simultaneously melting the substrate. As a result of this process, the metal content of the padding weld can be as high as several tens of percents. It is a method used to regenerate machine parts and improve the properties of the surface layer, increasing its resistance to abrasion, corrosion, erosion, and cavitation. It also supports the repair and creation of permanent protective coatings in the engineering, automotive, energy, and aerospace industries. This makes it possible to repair damaged parts instead of completely replacing them, saving time and production costs. Plasma surfacing technology is used for components that require high hardness and corrosion resistance under various environmental conditions. Plasma wire surfacing is not sufficiently presented and described in the current literature, which creates problems in determining the appropriate process parameters. The influence of variable plasma surfacing parameters on steel C45 significantly affects surfacing weld geometry, the dilution factor, and microhardness. Higher currents can increase the dilution factor, integrating more base metal into the weld pool, which may alter the chemical composition and mechanical properties of the weld. Variations in surfacing speed and heat input also affect the microhardness of the surfaced joint, with higher heat inputs potentially leading to softer welds due to slower cooling rates. Optimizing these parameters is essential to achieving desired surfacing weld characteristics and ensuring the structural integrity of C45 steel joints. This paper presents the influence of varying plasma surfacing parameters on the surfacing geometry, the dilution factor, and microhardness. The tests were carried out on a Panasonic TM-1400 GIII automated surfacing machine with CastoMag 45554S solid wire as the filler material. Flat bars of C45 steel were prepared, and then the variable parameters of the surfacing process were developed. Tests were carried out to determine the dilution factor, followed by microhardness measurements. The results showed a significant dependence of the effect of the parameters on the surfacing geometry and the dilution factor.

The effect of laser surface melting on the microstructure, microsegregation and solidification path of service-aged ECY768 cobalt-based gas turbine nozzle

In this study, the laser surface melting of cobalt-based superalloy ECY768, which has been in service for 40,000 h at a temperature of 1000 °C, has been investigated. Subsequently, laser surface welding and post-welding heat treatment is performed on the samples. This study was conducted in order to restore the microstructure of the damaged service-aged gas turbine nozzle to as-cast state. The results showed that by performing laser surface remelting, the microstructure of as-cast state can be approached. Also, the results of this study have investigated the weldability, microsegregation and solidification path of this superalloy, and it can be used in the repairing this superalloy in the industry. Laser surface melting was performed using a continuous wave fiber laser at various speeds of 10, 12, 14, 20, 50, and 70 mm/s. The microstructure and phase characteristics of the samples were examined using optical and scanning electron microscopes. Upon analyzing the macrostructure of the weld metal, it was observed that the depth of the melt zone at the speed of 12 mm/s is 585 ± 40 μm. In the investigating the microstructure of the solidification modes, namely planar, cellular, columnar dendritic, and equiaxed dendritic, it was observed that microsegregation occurs during laser welding of the samples due to the presence of heavy elements such as tantalum and tungsten. The solidification distribution coefficient for tantalum was calculated to be 0.37, which increased to 0.60 after the solution annealing heat treatment, resulting in an improved segregation behavior. Characterizing the surface hardness profiles of laser-melted samples it was observed that the hardness in the melt zone significantly increased compared to the base metal. The results of the current research indicate that the weldability (resistance to various welding defects, especially hot cracks) of the cobalt-based superalloy ECY768 is acceptable, and this process can be used for rejuvenating service-aged ECY768 cobalt-based gas turbine nozzle.

The electrochemical corrosion performance of aluminum alloys grade 6082-T6 weld repair

This research investigated the corrosion behavior of standard current metal inert gas weld repair for 6082-T6 aluminum alloy using ER5356 filler metal. The new and repaired (NW and RW) welds were studied. The welds comprised the weld metal (WM), the heat affected zone (HAZ) (solid solution and softened zones), and the base metal (BM). The study focused on investigating electrochemical corrosion using polarization and electrochemical impedance spectroscopy (EIS) methods in 3.5% NaCl solutions, especially in HAZ, including metallurgical and mechanical examinations. The BM containing an α-Al matrix with Al(Fe,Mn)Si and Mg2Si phases exhibited the maximum hardness (70–104 HV0.1). The WM hardness decreased (67–76 HV0.1) with the α-Al, β-Mg3Al2, and Mg2Si phases. Despite having comparable phases to BM, HAZs showed lower hardness (Solid HAZ: 70–82 HV0.1) due to more intermetallic phases. The RW’s softened HAZ revealed the minimum hardness (52–63 HV0.1) compared to that of the NW (55–70 HV0.1). Besides, the tensile strength of the RW (179.7 MPa) was also lower than that of the NW (174.4 MPa) because of the reheating effect. The electrochemical corrosion results indicated that the BM exhibited the maximum corrosion resistance (the lowest corrosion current density (icorr), the highest corrosion potential (Ecorr), and the charge transfer resistance (Rct)), followed by the HAZ and the WM, respectively. The softened HAZ demonstrated better corrosion resistance than the solid solution HAZ. Conversely, the over-aging effect reduced the softened zone’s pitting corrosion resistance (Ep) compared to the solid solution zone. The RW exhibited inferior corrosion resistance compared to the NW due to increased intermetallic phases, which was consistent with the mechanical results. However, the RW’s softened HAZ corrosion characteristics were inconsistent with its mechanical properties; its hardness and tensile strength were the lowest, but its corrosion resistance was not. Pitting corrosion was observed on the weld surfaces using the SEM.

Three-dimensional surface analysis of iron-based materials using synchrotron Mössbauer source

A novel three-dimensional surface analysis system for iron-based solid materials has been developed. This system is composed of a synchrotron Mössbauer source, an X-ray focusing device, a precision stage, a gas flow proportional counter for conversion electron measurements, and multiple multichannel scalers. The performance was evidenced by determining the spatial distribution of the iron oxide abundance on a laser-ablated iron foil surface. This system can be widely utilized as a powerful analytical tool in steel science for corrosion, welding, and laser surface modification.

Plume active control in high-power fiber laser welding based on high-speed shielding gas microbeam

Plume is an inherent physical phenomenon in fiber laser keyhole welding, negatively affecting welding quality. This paper proposes a new type of high-speed shielding gas microbeam (HSGM) based on the limitation of conventional shielding gas regulating plumes. The gas flow characteristics of the HSGM on the molten pool surface were explored using numerical simulation. Then, the coaxial double-layer shielding nozzle was trial-manufactured to clarify the regulation law for the HSGM on the plume. The gas velocity and pressure produced by the HSGM on the molten pool surface were positively correlated with the shielding gas flow rate, and the gas flow pattern was an acute triangle shape. The suitable HSGM can significantly restrain plume formation, improve the weld surface forming quality, increase the weld penetration depth (about 15.4%), and reduce the mass loss of the weld (about 58.7%). The significant blowing pressure effect of HSGM on plumes and splashes was the key to regulating the welding process. Compared with conventional shielding gas, the use of HSGM was significantly reduced.

A wall climbing robot based on machine vision for automatic welding seam inspection

With the ongoing progress of industrial technology such as shipbuilding, the importance of weld quality in industrial production is becoming increasingly prominent. Intelligent and automated welding seam inspection robots are more efficient than traditional manual inspection and can avoid dangerous accidents. This article describes the design of a welding seam inspection robot suitable for high-altitude ship operation. The robot uses machine vision and object segmentation models to automatically detect the position of welding seams, and uses a cubic polynomial to fit the welding seam path. The upper and lower computers of the robot communicate through WIFI transmission and TCP protocol, which can realize remote real-time detection of weld surface defects. In addition, this article designs a permanent magnet adsorption structure for robot high-altitude wall climbing, which has been verified through simulation and experimental verification. To verify the intelligence of the robot, this paper conducted performance analysis experiments on weld line recognition and tracking models and surface defect models. The experimental results showed that the average detection accuracy of the weld line recognition and tracking algorithm was 96.8%, and the average detection accuracy of surface defects in the three types of welds was 94.2%. The method proposed in this article combines two algorithms and a special robot structure, providing a new approach for the automated inspection of welds in large industrial products such as ships.

High-accuracy and lightweight weld surface defect detector based on graph convolution decoupling head

Abstract The essence of the difficulties for weld surface detection is that there is a lot of interference information during detection. This study aims to enhance the detection accuracy while keeping great deployment capabilities of a detection model for weld surface defects. To achieve this goal, an improved Yolo-GCH model is proposed based on the stable and fast Yolo-v5. The improvements primarily involve introducing a graph convolution network combined with a self-attention mechanism in the head part (i.e., GCH). This component focuses on improving the insufficient recognition capability of CNN for similar defects in complex environments. Furthermore, to address the presence of potentially ambiguous samples in complex welding environments, the label assignment strategy of simOTA is implemented to optimize the anchor frame. Additionally, a streamlined structure, aiming to improve model detection speed while minimizing performance impact, has been designed to enhance the applicability of the model. The results demonstrate that the cooperation of GCH and simOTA significantly improves the detection performance while maintaining the inference speed. These strategies lead to a 2.5% increase in mAP@0.5 and reduce the missing detection rates of weld and 8 types of defects by 32.9% and 84.1% respectively, surpassing other weld surface detection models. Furthermore, the impressive applicability of the model is verified across four scaled versions of Yolo-v5. Based on the proposed strategies, the FPS increases by more than 30 frames in the fast s and n versions of Yolo-v5. These results demonstrate the great potential of the model for industrial applications.

Mechanical characterization and microstructural evolution of Inconel 718 and SS316L TIG weldments at high temperatures

This study examines the impact of both constant and pulsed current on the tensile characteristics, micro-hardness of weld surface, and metallurgical properties of the Inconel 718 and SS316L weldments. The Tungsten Inert Gas (TIG) welding process utilized two distinct arc modes to combine incompatible metals. The pulse frequency was systematically adjusted within the range of 2 Hz–6 Hz in order to investigate its impact on the welding parameters. A tensile test was performed using a universal testing equipment under various temperature conditions, including room temperature and an elevated temperature of 350 °C. When the samples were welded at a frequency of 4 Hz, both the Ultimate Tensile Strength (UTS) and Yield Strength (YS) were greater compared to when the samples were welded at 2 Hz, 6 Hz, or a continuous arc mode. Furthermore, it was noted that the YS-to-UTS ratio was higher for the weldments produced at 4 Hz pulse frequency. The UTS of current and pulsed (4 Hz) modes at a temperature of 350 °C were determined to be 505 and 524 MPa, respectively. Pulse welding demonstrated a higher hardness number compared to steady welding due to the regulated rate of heat. The TIG weldments of Inconel 718 and SS316L demonstrated superior mechanical and metallurgical qualities when exposed to elevated temperatures. The practical implications of these findings are relevant to the fabrication of turbine discs and shafts.

Active control effect of shielding gas flow on high-power fiber laser welding plume

Plume are common physical phenomena in fiber laser keyhole welding and have serious negative effects on the welding process. Based on this, this paper explores the regulation law of conventional shielding gas flow on plume. The results show that the shielding gas has a very significant effect on the suppression of the slender part of the plume, and the greater the gas flow rate, the better the plume removal effect. The addition of the shielding gas makes the welding process more stable, the molten pool flows stably, and the frequency of spatter eruption is reduced. Under the experimental conditions, the optimal shielding gas flow rate is around 15 l/min, and the penetration depth and width are increased by about 10% and decreased by about 22%, respectively, compared with that without adding the shielding gas. Based on the gas flow simulation, the gas flow pressure (about 132 Pa) generated by an appropriate amount of shielding gas (about 15 l/min) can press the liquid column and spatter near the keyhole mouth into the molten pool to avoid the spatter eruption. Excessive shielding gas flow will interfere with the flow of the molten pool excessively, and the weld surface will show a serious undercut phenomenon.