Laser Welding Of Aluminum Alloys Research Articles

Predicting weld pool metrics in laser welding of aluminum alloys using data-driven surrogate modeling: A FEA-DoE-GPRN hybrid approach

Multi-physics computational models based on finite element analysis, offer detailed insights into the dynamics and metrics in the weld pool formed by laser welding. Conversely, data-driven surrogate models provide a cost-effective means to predict desired responses. These models establish statistical or mathematical correlations with input–output data, eliminating the need for additional simulations during design optimization. This study proposes a data-driven surrogate model, employing the Gaussian process regression network (GPRN), to predict weld pool metrics, such as weld width and depth of penetration in laser welding of aluminum alloy. A 3D computational fluid dynamics-based numerical model is initially constructed and experimentally validated to predict weld pool metrics. Subsequent experimental runs, guided by the design of experiments, include various configurations of process parameter settings. The developed numerical model computes weld pool metrics for each experimental run, forming a dataset for training and testing the GPRN model. The GPRN model is evaluated against simulated data, showing adequacy with a mean square error of 1.7 µm and mean absolute percentage error of 10−7, with experimental validation further confirming its accuracy, revealing a minimum error of 1.7%, a maximum error of 8%, and an average error of 3%. The key contribution and novelty of this study lie in the development of the hybrid data-driven model, which accurately predicts weld pool metrics while minimizing experimental and computational efforts.

Experimentally-guided finite element modeling on global tensile responses of AA6061-T6 aluminum alloy joints by laser welding

There are still some technical issues involved in laser welding of aluminum alloys, such as porosity, cracking, deformation, and so forth. In this study, AA6061-T6 sheets of 2.54 mm in thickness were welded by a disk laser in the bead-on-plate with two different welding parameter sets. Full penetration depths were achieved with decent surface appearances for both cases. The digital image correlation method was successfully applied in experiments to identify material model parameters of tensile welded specimens from various weldment regions. The identified parameters were utilized to numerically simulate the uniaxial tensile tests of laser-welded specimens. The effect of welded joint geometry on global tensile responses was investigated in experimentally-guided finite element modeling. With the help of X-ray computed microtomography, internal defects of the welded bead were detected and used as an input variable in the simulations. Strain development was observed through experimental and numerical data. The results showed that axial deformation was initiated at the top surface of welded metals. The considerable axial deformation occurred at the bottom surface (weld root) of the welded joint just before failure. The numerical results indicated that the geometry of welded joints greatly affected tensile responses. The results also concluded that the diameter of a single void significantly influenced tensile responses compared to its distributed location and the total volume of multiple voids with smaller sizes. Compared between the two sets of welding parameter sets used in this study, the welded joints of this particular AA6061-T6 material with the first parameter set of 2.40 kW laser power and 1.27 m/min traveling speed employed could give better tensile properties and be verified by both experimental and numerical results.

Deep learning-based monitoring system for predicting top and bottom bead widths during the laser welding of aluminum alloy

Weld bead geometry visually represents the result of the welding process. However, ensuring a consistent weld bead is not always guaranteed due to the instability of the welding process. In this study, we present a deep learning-based monitoring system that predicts both the top and bottom bead widths simultaneously during the multi-mode fiber laser welding of aluminum alloy 1050P-H16. From the predicted top and bottom bead widths, rich information about the welding process can be obtained. Our deep learning model was constructed based on the VoVNet27-slim architecture, which was successfully trained using weld pool images obtained coaxially by a small optical camera. We were able to obtain very clean images of the aluminum weld pool, which provided plentiful information about the weld pool and the resulting top and bottom bead widths. We attempted to use one or two weld pool images as input to study how an additional weld pool image can enhance prediction accuracy. It was found that the top bead width was accurately predicted by both the one- and two-image models. However, the two-image model showed a clear improvement in the prediction of the bottom bead width because the bottom bead width fluctuates more widely and cannot be directly seen from the top-side weld pool image. The optimal separation distance between the two input images was found to be −0.1 mm, with which additional weld pool information about the past was supplied to the model and the denoising effect was achieved. Monitoring changes in both top and bottom bead widths provides rich information regarding the welding process, and we believe that the presented deep learning–based approach can serve as an effective monitoring tool.

Simultaneous reduction in laser welding energy consumption and strength improvement of aluminum alloy joint by addition of trace carbon nanotubes

The widespread use of laser welded aluminum alloys in industrial production offers potential benefits to sustainable development and socio-economic progress. It simultaneously enhances the weld strength while reduces the energy consumption. Despite the promise of these alloys, research on reducing their energy consumption during laser welding is lacking. In this study, a dual effect of enhancing joint strength in 2A12 aluminum alloy and reducing energy consumption is achieved by the addition of trace carbon nanotubes (CNTs). The “welding efficiency" is defined and an energy consumption model for laser welding of aluminum alloys is developed. Next, the laser welding process with the addition of trace CNTs (LC) and the single laser welding process (LW) were compared and analyzed. The results indicate that adding trace CNTs can reduce energy consumption by more than 33 % and increase joint strength by 101 MPa. Furthermore, it is found that the LC process offers significant energy-saving advantages over other laser welding of aluminum alloy processes described in previous studies. These improvements is attributed to the increased laser absorption by the aluminum alloy induced by trace CNTs, as well as their residual presence in the joint, which acts as a strengthening medium. This work provides new insights and presents a novel approach for achieving low-carbon, high-quality welding of aluminum alloys.

Effect of beam oscillation frequency on porosity in laser welding of aluminum alloy lap-butt joints

Many investigations into laser oscillations for mitigating severe porosity in aluminum alloys have involved trading off penetration depth, potentially disrupting the porosity suppression mechanism. In this study, an oscillation laser butt-lap welding technique was designed, and the effect of oscillation frequency on cross-section morphologies and porosity rate was investigated while maintaining the constant weld depth. The findings unveiled that heightened oscillation frequencies led to diminished porosity levels, and this pattern remained consistent, even in cases where weld depths were extended. High-frequency laser beam oscillation enhanced the stability of the keyhole, increased the duration of the molten pool existence, and reduced porosity to 0.17%. Thus, this study offered significant insights into the impact of oscillation on laser welding of aluminum alloys.

Study on full-penetration laser welding of aluminum alloy under electromagnetic field support and subatmospheric pressure

Study on full-penetration laser welding of aluminum alloy under electromagnetic field support and subatmospheric pressure

Investigation on the keyhole/molten pool dynamic behavior during adjustable ring-mode laser welding of medium-thick aluminum alloy

Adjustable ring-mode laser welding (ARM) provides a new solution for the pore defects of aluminum alloy joints. However, the inhibition mechanism of ARM for porosity defects in the aluminum alloy welds with medium-thickness is still lacking. In this work, the dynamic behavior of the keyhole/molten pool and the formation/transport process of bubbles during adjustable ring-mode laser welding of medium-thick aluminum alloy are investigated by experiments and simulations. The results display that the laser power ratio of central-ring beam of 6:4, the porosity is 4.19 ± 2.32 %, which is reduced by 52.2 % compared with the weld by single laser welding (SLW) of the same penetration depth. The addition of ring beam helps to enlarge the tilt angle of the keyhole rear wall, which increases the ability of the keyhole wall to resist the impact of the molten pool. Besides, it also lowers the radial pressure gradient and the local variation of the keyhole wall. These reasons reduce the formation of pores. Furthermore, the main eddy current direction of the molten pool changes less frequently, and the melt flow velocity impacting the keyhole wall only changes in the range of 0–0.5 m/s (SLW: 0.25–0.75 m/s). This diminishes the fluid dynamic pressure which is the primary driving force of the bubbles. The velocity of the bubble moving away from the bottom of the keyhole is decreased and it is more likely to remelt the keyhole and escape under the action of the laser beam at the next moment. This work provides engineering application and theoretical reference value for the suppression of pore defects in laser welding of aluminum alloy in medium-thick plates.

Experimental analysis of overlap fiber laser welding for aluminum alloys: Porosity recognition and quality inspection

In recent years, laser welding has become increasingly popular in the manufacturing industry due to its advantages, including a narrow heat affected zone, low levels of distortion, the possibility of remote processing, and high welding speeds compared to conventional electric arc welding techniques. In the automotive industry, the need for overlapped joint welding, particularly for chassis assembly, has become increasingly relevant. The internal porosity detection and control in laser welding of aluminum alloys has gained significant attention. To support laser users in optimizing the welding process, this paper presents an experimental methodology followed by a phenomenological analysis of the quality of overlapped welded joints. The study focuses on the laser welding of two different aluminum alloy configurations (1.6-mm-thick AA 6061-T6 and 2-mm-thick AA 6061-T6) using three welding strategies (ScanLab remote laser welding system, Trumpf D70 laser head, and Precitec YW52 wobbling head) to evaluate single and multiple laser variants for process parameter tuning. Additionally, the paper discusses the use of X-ray technology as an offline monitoring method for porosity recognition, and analyzes laser beam characterization and beam profile shape to calculate beam distribution. Then, statistical analysis of all methods is conducted and regression analysis is performed. These findings provide valuable insights into the integration of laser welding technology in the automotive and surface transportation industries. The analysis of results indicates that as the spot size decreases, the real spot size changes more abruptly with increasing Z position, whereas with a larger spot size, the beam size remains stable up to +/- 20–30 mm in Z position due to the large lens. Porosity is mainly caused by either a too small spot size (in the absence of wobbling; ≤0.4 mm) or low travel speed (≤4.0–4.5 m/min). On the other hand, if the spot size is too large, hot cracking can occur in autogenous laser welding.

DBN-based online identification of porosity regions during laser welding of aluminum alloys using coherent optical diagnosis

As a typical serious defect during laser welding of aluminum alloys, porosity can significantly impair the performance of the weld seam. Real-time monitoring of porosity defect can provide guidance for feedback adjustment of welding quality to prevent the subsequent continued formation of porosity, which has attracted increasing attention. This paper implements the deep learning-based online identification of porosity regions using coherent optical diagnosis. Considering the formation mechanism of porosity, a monitoring platform including a coherent optical sensor is established to measure the keyhole 3D morphology and extract the keyhole depth as the coherent optical signal. The acquired keyhole depth signal is processed by ensemble empirical mode decomposition, and it is discovered that there is a segmentation threshold in the reconstructed signal to separate the porosity regions and the non-porosity regions. A deep belief network is constructed to complete the reception of the reconstructed keyhole depth signal and the response of the prediction state, realizing the online identification of the porosity regions. The results show that the identification model has high accuracy, and the validity verification demonstrates the reliability of the proposed method.

Hot-Cracking Mechanism of Laser Welding of Aluminum Alloy 6061 in Lap Joint Configuration.

Laser welding, known for its distinctive advantages, has become significantly valuable in the automotive industry. However, in this context, the frequent occurrence of hot cracking necessitates further investigation into this phenomenon. This research aims to understand the hot-cracking mechanism in aluminum alloy (AA) 6061, welded using a laser beam in a lap joint setup. We used an array of material characterization methods to study the effects of processing parameters on the cracking susceptibility and to elucidate the hot-cracking mechanism. A laser power of 2000 W generated large hot cracks crossing the whole weld zone for all welding speed conditions. Our findings suggest that using a heat input of 30 J/mm significantly mitigates the likelihood of hot cracking. Furthermore, we observed that the concentrations of the alloying elements in the cracked region markedly surpassed the tolerable limits of some elements (silicon: 2.3 times, chromium: 8.1 times, and iron: 2.7 times, on average) in AA6061. The hot-cracking mechanism shows that the crack initiates from the weld root at the interface between the two welded plates and then extends along the columnar dendrite growth direction. Once the crack reaches the central region of the fusion zone, it veers upward, following the cooling direction in this area. Our comprehensive investigation indicates that the onset and propagation of hot cracks are influenced by a combination of factors, such as stress, strain, and the concentration of alloying elements within the intergranular region.

Feasibility Study of Handheld Laser Welding Technology for Small Thickness Aluminium Alloys

Handheld laser welding with filler material is an interesting alternative for TIG and MIG/MAG welding in aesthetic parts of small thicknesses, due to its high versatility, speed of application, low deformability and aesthetic finish. The novelty of this study lies in the analysis of the feasibility of this process for welding aluminium alloys of low thickness (2mm), commonly welded by GTAW or GMAW processes. Due to its high sensitivity to heat, laser welding of aluminium alloys is always accompanied by defects such as porosity and cracks. In this work aluminium-magnesium alloy sheets (5754 H111) were joined using fillet weld, butt weld and cornice weld configurations. The appearance, microstructure, porosity and mechanical properties were analyzed through non-destructive and destructive tests. The results of the external aspect of the samples showed a very low distortion and deformation of the material; however, the macrographic analysis showed abundant internal porosity. In the case of the fillet and cornice welding this porosity was within the applicable standard, and in the case of the butt-welded samples, tensile tests results proved the validity of the process.

Numerical analysis of the effect of energy distribution on weld width during oscillating laser welding of aluminum alloy

The weld morphology of aluminum alloy oscillating laser welding has an important influence on the quality of welded joints. To understand the formation process of the weld morphology, the three-dimensional numerical simulation model and energy distribution model for circular shaped oscillating laser welding of 6061 aluminum alloy are developed in this paper to analyze the characteristics of weld morphology and the effect of the energy distribution on the weld width. The cross section of the weld and the energy distribution on the processing surface are obtained under the conditions of different oscillation frequencies. It is found that the left width of the weld is larger than the right width of the weld and the energy density on the left side of the weld is more concentrated than that on the right side of the weld. With the oscillation frequency increases, the weld width and peak of energy density decrease. Furthermore, the formation mechanism of the difference in weld width is revealed based on the energy distribution law of the oscillating laser welding process, which is of great significance for improving the quality of aluminum alloy oscillating laser welding.

Investigation of microstructure evolution on different planes in laser welding of aluminum alloy

The solidification behavior of a molten pool is a critical factor affecting the mechanical properties of welded joints. This paper develops a multi-scale model combining the macroscale heat transfer and fluid flow model with the microscale phase field model for calculating the microstructure evolution on two different planes that are perpendicular to the thickness direction in the laser welding of the aluminum alloy. To obtain the time-varying temperature gradient (G) and solidification velocity (R) used in the simulation, a transient solidification conditions model is proposed. These models are validated by comparing the simulation results with the experimental results. The results indicate that G decreases, while R increases during solidification process. G/R decreases on both two planes, which results in the transformation of the microstructure from planar to cellular and then to the columnar grain. Additionally, it is found that the primary dendrite arm spacing of columnar grains on the lower plane is smaller, which is related to lower G−1/2R−1/4.

Numerical and experimental study on keyhole dynamics and pore formation mechanisms during adjustable-ring-mode laser welding of medium-thick aluminum alloy

Keyhole induced-pore is one of the biggest challenges in laser welding of aluminum alloys. A shaped laser controlling strategy, ring-mode laser, has shown the possibility of reducing porosity in welding due to its potential to enlarge keyhole openings and improve the stability of the keyhole. However, few attempts have been made to reveal the influence of ring-mode laser on keyhole dynamics and pore formation. This paper quantitatively investigated porosity improvement during adjustable-ring-mode laser welding (ARM-LW) of aluminum alloys and analyzed keyhole dynamics and porosity formation mechanisms using a validated model. Experimental results indicate that porosity can be dramatically reduced when compounding a ring laser beam over the Gaussian beam. As the core/ring power ratio adjusts from 10:0 to 5:5, the porosity decreases significantly and remains lower (1.73%∼2.58%) while ensuring a similar melt depth (5∼6 mm). Simulation results demonstrate that two mechanisms work synergistically to suppress porosity: (1) The ring-mode laser contributes to decreasing keyhole collapse and regulating melt pool flow, hence reducing pores created at the Gas-Liquid interface (G/L-pore); (2) The ring-mode laser facilitates reducing the frequency and depth of keyhole into the melt pool, thus minimizing pores created at the Liquid-Solid interface (L/S-pore). This work can guide the porosity suppression during laser welding of aluminum alloys and is of significant theoretical meaning and application value.

The Analysis of Energy Distribution Characteristics of Molten Pool in Welding of Aluminum Alloy with Oscillating Laser

The energy distribution in molten pool is highly related to the quality of the weld formation in aluminum alloy welding. The forming defects in the weld are often improved by adjusting the molten pool dynamic behaviors affected by energy distribution. Therefore, the energy distribution characteristics in the molten pool during the welding of aluminum alloy with oscillating laser in the “∞” shaped path are explored in this paper. The pore defects are found to be greatly reduced in welds from the oscillating laser welding of aluminum alloy compared to those from non-oscillating laser welding. The corresponding distribution characteristics of energy in the molten pool of welding with oscillating laser are obtained and analyzed. The dynamic behaviors and forming process of welds under welding conditions of different distribution characteristics of energy in the molten pool are discussed. The obtained results are in good agreement with the experimental results. Therefore, the proposed method can provide the desired energy distribution for stable dynamic behaviors of molten pool to improve welding quality.

Keyhole stability and surface quality during novel adjustable-ring mode laser (ARM) welding of aluminum alloy

Aims at keyhole instability and poor surface-quality in welding of aluminum alloy, a novel laser technology has been studied on welding of Al 6061. The novel laser beam consists of a ring part and a center part. Different power ratio of ring laser beam to center laser beam and different kind of laser beam welding experiments have been conducted, respectively. The keyhole stability and surface quality were analyzed by using a high-speed camera and a confocal sensor accordingly. Additionally, the energy absorption rate was studied by analyzing the penetration and fusion area of cross-section. Experimental results showed that the ring laser beam provided great stability on the center laser-induced keyhole in high-speed dual-mode ring/center laser welding of aluminum. The stability effects can be improved by increasing the ring power in dual-mode ring/center laser welding of aluminum alloy, and the stabilized effect would contribute to the high-surface quality on welding of aluminum alloy. Furthermore, the combination of ring laser and center laser (Gaussian laser) greatly improved the welding efficiency due to its synergistic effects on process status in the ARM laser welding process. This work provided a basic research to both scientist and engineer on the mechanism of ARM laser welding aluminum alloy.

Quantitative Evaluation of Penetration State in Pulsed Laser Welding of Aluminum Alloys Based on Acoustic‐Wave Time‐Frequency Characteristics and Deep Learning

Quantitative Evaluation of Penetration State in Pulsed Laser Welding of Aluminum Alloys Based on Acoustic‐Wave Time‐Frequency Characteristics and Deep Learning

Cross-attention-based multi-sensing signals fusion for penetration state monitoring during laser welding of aluminum alloy

A precision multi-sensor monitoring strategy is required to meet the challenges posed by increasingly complex products and manufacturing processes during laser welding. In this work, an acoustic sensor and a photoelectric sensor were adopted to collect the signals during the laser welding of aluminum alloy. The dataset was divided into three categories according to the morphologies of the top and back sides. The cross-attention fusion neural network (CAFNet) was proposed to interactively capture photoelectric and acoustic information for effective quality classification without prior time–frequency analysis and feature learning. Its effectiveness and superiority were compared with the five types of deep learning (DL) based methods. It demonstrates that the proposed CAFNet method achieved a mean testing accuracy of 99.73% and a standard deviation of 0.37%, which outperforms other compared models. At the same time, the proposed CAFNet achieved the highest average testing accuracy of 94.34% when utilizing limited and imbalanced data, which suggested that the proposed method has stronger robustness than other methods. This approach is a new paradigm in the monitoring of laser welding and can be exploited to provide feedback in a closed-loop quality control system.

Numerical and experimental study on melt-pool heat transfer and weld characteristics in dual-mode fiber laser welding of aluminum alloy

A dual-mode fiber laser consisting of center and ring beams has attracted significant attention in the laser welding field owing to its ability to stabilize melt pools and reduce defect formation. In this study, a dual-mode fiber laser was adopted for butt welding of an aluminum alloy. Experimental and numerical investigations were conducted to analyze the weld characteristics and heat transfer phenomena during the process. The use of both the center and ring beams produced a funnel-like weld shape because of the low ring beam intensity, resulting only in the melting of the upper part of the workpiece. As the ring beam power increased, the temperature gradient near the solidification front, acting as a driving force for fluid flow, decreased. This contributed to the relatively gentle fluid flow and the smooth bead surface. It was also found that an increase in ring power lowered the cooling rate of the melt zone near the weld edge. Therefore, the average grain size of the weld zone increased with an increase in the ring power. The results of this study provide fundamental insights into the mechanism of dual-mode fiber laser welding.

Online porosity prediction in laser welding of aluminum alloys based on a multi-fidelity deep learning framework

Online porosity prediction in laser welding of aluminum alloys based on a multi-fidelity deep learning framework