Weld Penetration Depth Research Articles

A Study on the Green Laser Weldability of Copper-aluminum Battery Materials

Copper is widely utilized in electric vehicle batteries due to its excellent electrical conductivity, lightweight, and excellent corrosion resistance. However, copper has a high reflectivity of about 97% for infrared lasers, which makes it difficult to achieve stable welding quality. This study investigated using a green laser to weld nickel-coated copper and aluminum materials. After performing welding by changing the laser power and scan speed, the weld cross-section was observed with an optical microscope, and it was confirmed that the welding penetration depth and bead width increased as the heat input increased. The spatter on the bead surface and defects such as pores and cracks in the weld were caused by excessive heat input. Analysis of the weld cross-section using SEM-EDS showed that high heat input increased the formation of intermetallic compounds including CuAl2 and Cu9Al4. The mechanical properties of the weld were examined using a shear tensile test. The analysis results showed that intermetallic compounds caused brittleness in the weld joint, which lowered mechanical properties and caused defects such as pores and cracks. P60 (1.2 kW, scan speed: 250 mm/s), P80 (1.6 kW, scan speed: 375 mm/s), and P100 (1.2 kW, scan speed: 375 mm/s) were examples of excellent mechanical quality. The fastest welding condition, P100 (power: 2 kW, scan speed: 450 mm/s), was suggested as the most efficient welding condition.

Study on penetration depth in laser welding: A process information database-based control strategy and OCT measuring verification

Penetration depth acts as a crucial indicator reflecting laser welding quality, thus the control of its stability and the perception of its fluctuation state are increasingly garnering attention. This paper proposes a process information database-based control strategy for penetration depth, and the control validity is verified through penetration depth detection utilizing optical coherence tomography (OCT). The process information database stores diverse expected penetration depth knowledge formed by a substantial quantity of varying welding speeds with fixed other process parameters under undisturbed welding conditions. In the database, the stable average values inside the standard penetration depth information and the corresponding heat input (HI) values are connected and mapped via an artificial neural network (ANN). In response to abnormal variations in the penetration depth curve caused by interferences during welding, according to the HI gap predicted by the trained ANN from the penetration depth gap arising from the curve deviation, the control unit can calculate the new welding speed required to feed the penetration depth curve back to within the steady fluctuation range. Based on OCT, the keyhole depth signal is acquired, and a deep belief network is built to predict the penetration depth curve via the correlation between the reconstructed keyhole depth obtained by ensemble empirical mode decomposition and the penetration depth. This detection method demonstrates that the penetration depth curve can be controlled accurately. Finally, a closed-loop real-time feedback control system for penetration depth is established.

Evaluating edge joint preparation impact on penetration depth in laser-arc hybrid welding

Nowadays, conventional welding technologies such as submerged arc welding (SAW) are still used in most heavy-steel industries. This type of traditional technology means that welding takes up a large part of the productive time. As a solution to this problem, there are welding methods, such as Laser-Arc Hybrid Welding (LAHW), that have the potential to reduce the cost of manufacturing large steel structures. This is possible due to the reduced number of weld passes required to join thicker steel sections, as large thicknesses can be welded in one or a few passes.A problem with LAHW is achieving satisfactory quality. For this reason, it is essential to study the starting conditions, e.g. edge joint preparation. The target of this research work is to find out the relationship between the penetration value of the weld bead obtained and the edge joint preparation. The evolution of the molten pool and the behavior of the molten material in the joint is discussed for the different edge joint preparation configurations. The effect of the roughness is that it affects the wetting of the molten material in the joint, which would affect the penetration result, together with the gap and air volume gap used in the joint. Cut-wire is also used in the research, in samples that presented a larger air volume gap. The behavior of the molten metal inside the joint in this case is also discussed. In addition, the quality of the weld beads has also been determined by making macrographs, microstructural analysis, X-ray, microhardness profiles, tensile test and Charpy test. Some pores and cracks have been found, although destructive tests show adequate behavior of the weld bead. It is possible to elucidate from the findings that as the roughness, gap and/or air volume gap of the edge joint increases, the penetration value obtained increases. Cut-wire samples obtained full penetration.

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.

Formation and mechanical properties of AZ31B magnesium alloy welds by power-modulated oscillating laser

an energy-space modulated laser was proposed in welding workpieces with AZ31B magnesium alloy to enhance the efficiency of heat transfer and reduce defects of welds, and the proposed laser was power-modulated oscillating laser (PMOL). To validate the performance of the proposed technique, non-penetration welding and butt welding were conducted on the workpieces with a thickness of 5 mm. The impact of power-modulation parameters was investigated at the aspects of micro-structures, appearance, and mechanical properties of welds. The results showed that in comparison with a conventional laser (CL) or circular oscillation laser (COL), an energy-space modulated laser led to (1) an increased depth of weld penetration and (2) an enhanced coupling efficiency of laser energy. The parameters of power modulation could be optimized to reduce the defects of welds such as spatter, underfill, and thick fish scales significantly reduced; it refined the equiaxed grains in the center area of weld. When the frequency and amplitude of power-modulation were set as 50 Hz and 500 W, respectively, the mechanical properties of the weld were improved with the ultimate tensile strength of 238 MPa and an elongation ratio of 13.9 % which were 96.1 % and 58.7 % of those of the base material (BM), respectively. In comparison with the results welded by CL and COL, the ultimate tensile strength by PMOL was increased by 13.9 % and 4.4 %, and the elongation was increased by 54.4 % and 8.6 %, respectively.

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.

Comparative Numerical Analysis of Keyhole Shape and Penetration Depth in Laser Spot Welding of Aluminum with Power Wave Modulation

Keyhole mode laser welding is a valuable technique for welding thick materials in industrial applications. However, its susceptibility to fluctuations and instabilities poses challenges, leading to defects that compromise weld quality. Observing the keyhole during laser welding is challenging due to bright process radiation, and existing observation methods are complex and expensive. This paper alternatively presents a novel numerical modeling approach for laser spot welding of aluminum through a modified mixture theory, a modified level-set (LS) method, and a thermal enthalpy porosity technique. The effects of laser parameters on keyhole penetration depth are investigated, with a focus on laser power, spot radius, frequency, and pulse wave modulation in pulsed wave (PW) versus continuous wave (CW) laser welding. PW laser welding involves the careful modulation of power waves, specifically adjusting the pulse width, pulse number, and pulse shapes. Results indicate a greater than 80 percent increase in the keyhole penetration depth with higher laser power, pulse width, and pulse number, as well as decreased spot radius. Keyhole instabilities are also more pronounced with higher pulse width/numbers and frequencies. Notably, the rectangular pulse shape demonstrates substantially deeper penetration compared to CW welding and other pulse shapes. This study enhances understanding of weld pool dynamics and provides insights into optimizing laser welding parameters to mitigate defects and improve weld quality.

Improvement in weld quality of Al and Cu joints using dual-beam laser welding

The high weld quality of dissimilar aluminum (Al)/copper (Cu) joint is essential to improve the reliability of connecting components in secondary batteries. This study was aimed at enhancing the weld quality of dissimilar AlCu joints to connect tab-to-busbar in secondary batteries. AA1050 and Ni-coated Cu (C1100) sheets were lap-welded using dual-beam laser welding with a continuous-wave (CW) laser for welding and a pulsed laser for preheating. Consequently, the weld quality was investigated by characterizing the morphology, microstructure, and mechanical and electrical properties of the joints. For comparison of the weld quality, single-beam welding was also performed. Soundly welded joints were achieved using a dual-beam at a CW laser power range of 1000–1400 W for fixed pulsed laser power and welding speed of 100 W and 80 mm/s, respectively. Microstructural analysis of the weld indicated that the upper weld metal (WM) comprised α-Al and AlCu eutectic phases, whereas the lower WM exhibited mixed morphology of different phases including Al2Cu, AlCu, Al3Cu4, and Al4Cu9. Further, the electrical resistance was linearly correlated with weld penetration depth, exhibiting a minimum of 352.3 μΩ against a penetration depth of 341.7 μm. In addition, The Vickers microhardness and lap shear tensile testing of soundly welded sample (A4) exhibited an average hardness value of 921.7 HV in the lower WM, and the average tensile load for the welded sample was 247.4 N. This study provides valuable insights for improving the weld quality of reliable AlCu dissimilar joints for connecting tab-to-busbar in secondary batteries.

Controlling the weld penetration depth of laser beam micro welding by using an iterative learning approach

AbstractIn order to meet the increasing demand for high‐speed joining processes, laser beam micro welding is used to reproducibly weld metallic joining partners such as steel. Long weld seams or high cycle speeds, however, remain a challenge to achieve a constant welding depth throughout the entire welding process without major fluctuations. This paper shows the development and evaluation of a weld penetration depth control system based on interferometric measurement of the depth of the vapor capillary. High path speeds and small weld depths are challenging for real‐time depth control. Therefore, the offline data of the interferometric measurements are used to implement an iterative learning control of the weld penetration depth. The quality of the control is verified by welding with and without spatial power modulation on 1.4301 steel while following a linear and sinusoidal trajectory.

Online Detection of Laser Welding Penetration Depth Based on Multi-Sensor Features.

The accurate online detection of laser welding penetration depth has been a critical problem to which the industry has paid the most attention. Aiming at the laser welding process of TC4 titanium alloy, a multi-sensor monitoring system that obtained the keyhole/molten pool images and laser-induced plasma spectrum was built. The influences of laser power on the keyhole/molten pool morphologies and plasma thermo-mechanical characteristics were investigated. The results showed that there were significant correlations among the variations of the keyhole-molten pool, plasma spectrum, and penetration depth. The image features and spectral features were extracted by image processing and dimension-reduction methods, respectively. Moreover, several penetration depth prediction models based on single-sensor features and multi-sensor features were established. The mean square error of the neural network model built by multi-sensor features was 0.0162, which was smaller than that of the model built by single-sensor features. The established high-precision model provided a theoretical basis for real-time feedback control of the penetration depth in the laser welding process.

Optimization and GRA prediction of Al–Cu pulsed laser welding process based on RSM

In this paper, the process parameters of pulsed laser welding of Al–Cu are studied using response surface methodology (RSM) and grey relation analysis (GRA) to propose optimal directions for lap-shear strength of the joints. A single-factor experiment was conducted to find the suitable process parameter windows. The RSM models were established and analyzed with laser power, welding speed, pulse width, and frequency as inputs and joint lap shear, interfacial weld width, and weld-penetration-depth as outputs. With the use of GRA of interfacial weld width and weld penetration depth with the lap-shear force of joints, the improved direction for the lap-shear force of joints can be proposed.

Penetration depth, phase balance and corrosion behaviour in activated TIG welding of UNS S32205

The aim of this research is to investigate the impact of a flux containing 80% TiO2 and 20% CeO2, under protective atmosphere (100% Ar, 98% Ar-2% N2, and 95% Ar + 5% N2) on penetration depth, phase equilibrium, and corrosion behaviour of autogenous A-TIG welds generated at constant current density. The reason for choosing cerium in the flux composition and nitrogen in the shielding gas is their effect on the phase balance of austenite and ferrite in this alloy. Metallography, ferritoscopy, and potentiometry were employed in the examination of the welds. The use of a two-component flux increased the penetration depth in TIG welding by up to 87%. Adding 2% and 5% nitrogen gas to the shielding gas in active TIG welding further increased the penetration depth to 117% and 130%, respectively. The results of ferritoscopic analysis reported the amount of austenite in the base metal and conventional TIG weld as 48% and 32%, respectively. However, the use of two-component flux increased the amount of austenite in the weld metal to 39%. Additionally, the addition of 2% and 5% nitrogen to the shielding gas in active TIG welding increased the amount of austenite in the weld metals to 60% and 76.6%, respectively. According to cyclic potentiodynamic polarization studies, active TIG welding with different nitrogen gas concentrations showed improved general and pitting corrosion properties in weld metals compared to conventional TIG welding. Consequently, weld metal resulting from active TIG welding with 2% nitrogen gas exhibited corrosion properties almost identical to that of the base metal.

A Study on the Weldability of Cylindrical Secondary Battery Material using Green Laser

This study investigates a green laser welding on a nickel-coated copper-mild steel material used in an electric vehicle battery. The laser power and scan speed were varied, and through optical microscopy, it was demonstrated that excessive heat input led to increased weld penetration depth and bead width. Regarding defects, excessive heat input caused the formation of oxide, spatter on the bead surface, as well as porosity and cracks inside the weld penetration depth. The mechanical properties were evaluated through shear stress and microhardness measurements, indicating that as the heat input increased, the mechanical properties improved for the sample welded under the 2 kW condition. Considering the fire risk (occur at weld penetration depth over 50%) and joining aspects (start at weld penetration depth higher 20%), the optimal conditions were set as 1.6 kW and 300 mm/s. This optimized condition was set as the reference for monitoring. Based on the optimized condition, the results shown that an increase in heat input led to increased plasma and temperature signals, and an increase in scanning speed resulted in an increase in reflected light signal.

Numerical study on welding residual stress by double-sided submerged arc welding for orthotropic steel deck

The orthotropic steel deck (OSD) is susceptible to fatigue damage under repeated traffic loads, and the welding residual stress (WRS) is an important factor contributing to fatigue damage in OSD. The study on WRS and its distribution is essential for the accurate estimation of the fatigue resistance of U rib-to-deck (RTD) welded joints. A recent emerging double-sided submerged arc welding (DSSAW) technology can generate higher welding temperatures in U rib and deck than traditional arc welding technology, and consequently generate higher welding penetration depth for welding thicker base metal. However, the WRS generated by the DSSAW technology has not yet been investigated. In this study, the finite element (FE) model of OSD with RTD welded joints is established by using a thermo-mechanical sequential coupling calculation method, which is first time to study the WRS generated by DSSAW. Also, the distribution characteristic and generation mechanism of WRS at the RTD welded joints are discussed and analyzed. Moreover, the effects of model length on the WRS simulation results are discussed, and the effects of the deck thickness, the U rib thickness, and the welding sequence on the WRS at RTD joints are analyzed. The findings in this study can help to an in-depth understanding of the WRS generated by the new DSSAW and support further studies on the fatigue resistance of OSD.

Welding investigation of Hastelloy C-276 and parametric optimization using integrated MRA-TLBO algorithm during A-TIG process

A-TIG welding is a modified form of GTAW process that has become popular due to its ability to create high-quality welded joints with minimal cracks and distortion. This technique is commonly used to join various metals, including stainless steel, aluminum, titanium, and nickel alloys like Hastelloy C-276, which is used in fabrication of complex components across marine, nuclear, aerospace, and chemical industries. In this investigation, A-TIG welding of Hastelloy C-276 was studied using three parameters - welding current, welding speed, and gas flow rate - at three distinct levels. The impact of these parameters were analyzed on two responses, namely penetration depth and width of weld. Macrostructural investigation, sensitivity analysis, and parametric studies revealed that welding current (I) had the most influence, followed by speed of welding (S) and flow rate of gas(G). Full quadratic multiple regression analysis-based models were developed for both responses, which were found to be suitable with a higher coefficient of determination and an average percentage error of 2.165% and 2.624%, respectively. Additionally, a teaching learning based optimization algorithm was integrated with these models to identify the most effective A-TIG parameter combination for higher penetration depth and lower weld width. The MRA-TLBO integrated approach resulted in an optimal parametric combination of I (170A), S (180 mm min−1), and G (11.37 l min−1) that resulted in a penetration depth and weld width of 4.503 mm and 4.684 mm, respectively. Validation at this optimal setting showed an improvement of 3.365% and 1.284% for weld width and penetration depth, respectively, suggesting the robustness of the developed methodology.

Monitoring weld penetration of laser-arc hybrid welding joints without full-penetration requirement based on deep learning

In-situ monitoring weld penetration of laser-arc hybrid welding (LAHW) joints without full-penetration requirement is challenging since no back reinforcement occurs. The novelty of this study is to develop convolutional neural network (CNN) models for real-time monitoring of weld penetration in LAHW based on front weld pool images. A dataset, including front weld pool images and corresponding weld penetration labels determined by weld cross-sections, is established by conducting weld tests under different laser powers. CNN classification models, i.e., AlexNet, ResNet18, and ResNet50, are trained and validated by the dataset. The ResNet18 model can classify four weld penetration states with the highest accuracy, achieving 99%. Then, a regression model is constructed to predict the weld penetration depth via the ResNet18 model parameters. The comparison between predicted and actual penetration depths indicates that 98.8% of the errors are less than 0.5 mm, and 61.43% are less than 0.1 mm.

Monitoring laser weld penetration status from the optical signal

Spectrometers have demonstrated their value in laser welding by facilitating the comprehension of welding dynamics and the identification of defects. However, the complex interaction between the laser beam and the material being welded makes it difficult for spectrometers to accurately capture the depth and extent of weld penetration, predominantly because plasma formation during welding interferes. This study presents an innovative approach that integrates laser technology, spectrometers, and advanced data analysis methods to classify and characterize various penetration types in pulse laser welding procedures, with notable computational efficiency. The research entailed the execution of an experiment on a boron steel plate, wherein peak power (1000-1200 kW), pulse duration (2-4 ms), and pulse repetition rate (25-50 Hz) were systematically varied to achieve diverse penetration conditions. Two categories of joints were identified based on their depth of penetration through careful analysis of the collected data. The investigation demonstrated a positive correlation between the depth of weld penetration and the increment of laser energy, with peak power ranging from 1000 kW to 1200 kW. Consequently, an elevation in light intensity was observed related to deeper weld penetration. The information is essential for understanding the relationship between laser energy and weld penetration, highlighting the importance of controlling laser parameters to achieve desired welding results. The spectrums were analyzed using Principal Component Analysis (PCA) to distinguish between different welding conditions. Overlap was observed between data from different weld conditions due to limitations imposed by the restricted dataset. Expanding the sample size can rectify this limitation and improve the accuracy and dependability of analytical outcomes. This study’s results provide valuable insights into optimizing welding parameters and improving understanding of the welding process, specifically in Tailor Weld Blanks. The findings offer potential for improving welding quality and strengthening lightweight components in high-performance industries like aerospace and automotive engineering.

Characteristics of welding laser beam and its influence on weld forming coefficient

Laser welding is a very complicated process. At present, there is no systematic research on the relationship between welding parameters and forming coefficient. By studying the internal relationship between laser parameters and the characteristics of welding laser, laser beam indexes, such as focusing index, are defined. They are simplified to a few laser parameters so as to facilitate the study of the influence of welding parameters on the forming coefficient. The results show that material, assembly gap, laser power and welding speed have great influence on weld penetration. When the laser power density reaches 106J/cm2, the characteristics of deep penetration welding appear. Under the condition of constant clearance, the weld depth increases with the increase of t/b. The weld penetration increases with the increase of laser power and tends to be stable when the welding speed is 12mm/s. Different materials also have a certain influence on the weld penetration depth. Under the same conditions, X6CrNiTi1810 obtains greater penetration depth, indicating that physical and chemical properties of materials are also one of the factors affecting the penetration depth. The mechanism and condition of laser welding were analysed. The relationship between laser absorptivity of sheet surface and physical properties of the materials is also studied and then obtained. The study will provide theoretical guidance for laser welding process design and welding parameter selection of steel plate.

Research on welding defect examination technique based on phased array ultrasonic for high voltage transformer oil tank welds

Oil tank of high voltage transformer plates. During welding and operation, defects such as incomplete fusion, incomplete penetration , air holes and cracks may be produced which influence the integrity and density of the welds and the whole tank. In order to test the integrity of the shell weld of high-pressure transformer box and ensure no leakage of transformer oil, the phased array testing technology is used to detect the defects of the butt weld of the transformer oil tank. The characteristics of weld defect detection under the condition of incomplete penetration were studied, and the sound beam accessibility, process selection principle and probe selection principle were theoretically analyzed. The test tests were carried out on the artificial samples of the butt weld of the transformer oil tank plate. The results show that the phased array can effectively detect the defects in the weld of transformer tank shell under the condition of incomplete welding, and the imaging results are intuitive and easy to judge, which can effectively evaluate the integrity of transformer tank weld. During the process selection, the probe-wedge combination with appropriate front distance and detection Angle should be selected according to the wall thickness, weld penetration depth and crown width of the transformer oil tank. During defects judgment, the interference of structure echo wave and incomplete penetration area should be considered. The assistant defect positioning analysis based on incomplete penetration is also suggested.

Исследование оптимальных параметров наплавки при восстановлении валов электродвигателей

Repairing damaged or worn motor shafts is an important part of the restoration work faced by many industrial plants. In the manufacturing sector, keeping electric motors running optimally is essential to keeping production running smoothly and efficiently. To reduce the cost of purchasing new electric motor shafts in the event of their breakdown or wear, industrial enterprises use surfacing. The quality of the deposited layer is determined, among other things, by the surfacing method and its technological modes. This article discusses the problem of obtaining a high-quality layer when restoring electric motor shafts by surfacing in three ways: manual surfacing, semi-automatic surfacing in a protective gas environment and automatic submerged surfacing. The advantages and disadvantages of each surfacing method are determined. Optimal technological modes of surfacing (current strength and welding arc voltage) were established using various methods based on an experiment with determination of geometric parameters (weld width, weld height, weld penetration depth) and physical and mechanical properties of restored surfaces (hardness).