Evaluation on Spot Weld Models in Structural Dynamic Analysis of Automotive Body in White

Spot weld models are widely used in finite element analysis（FEA） of automotive body in white（BIW） to predict static,dynamic,durability and other characteristics of automotive BIW.However,few researches are done on evaluation of the validity of these spot weld models in structural dynamic analysis of BIW.To evaluate the validity and accuracy of spot weld models in structural dynamic analysis of BIW,two object functions,error function and deviation function,are introduced innovatively.Modal analysis of Two-panel and Double-hat structures,which are the dominated structures in BIW,is conducted,and the values of these two object functions are obtained.Based on the values of object functions,the validity of these spot weld models are evaluated.It is found that the area contact method（ACM2） and weld element connection（CWELD） can give more precise prediction in modal analysis of these two classical structures,thus are more applicable to structural dynamic analysis of automotive BIW.Modal analysis of a classical BIW is performed,which further confirms this evaluation.The error function and deviation function proposed in this research can give guidance on the adaptability of spot weld models in structural dynamic analysis of BIW.And this evaluation method can also be adopted in evaluation of other finite element models in static,dynamic and other kinds of analysis for automotive structures.

An approach of artificial neural network to robotic welding process modelling

Artificial neural networks(ANNs)have been investigated for application to robotic welding process.Two types of the ANN models are described.The first is a static modeling approach for the pre-setting of robotic welding parameters, and the other is a dynamic modelling for real time feedback control of robotic welding.These models map the relationship between the weld bead geometry and welding process parameters.Some basic concepts relating to neural networks are discussed. The performance of neural networks for modelling is discussed and evaluated by using actual robotic welding data.It is concluded that neural network is capable of modeling readily and quickly a multivariable welding process and the accuracy of neural networks modelling is comparable with the accuracy achieved by the statistical scheme. The choice between ANN and statistical models will depend on the application and control strategy used.

Quantitative Metal Magnetic Memory Reliability Modeling for Welded Joints

Metal magnetic memory（MMM） testing has been widely used to detect welded joints. However, load levels, environmental magnetic field, and measurement noises make the MMM data dispersive and bring difficulty to quantitative evaluation. In order to promote the development of quantitative MMM reliability assessment, a new MMM model is presented for welded joints. Steel Q235 welded specimens are tested along the longitudinal and horizontal lines by TSC-2M-8 instrument in the tensile fatigue experiments. The X-ray testing is carried out synchronously to verify the MMM results. It is found that MMM testing can detect the hidden crack earlier than X-ray testing. Moreover, the MMM gradient vector sum K_（vs） is sensitive to the damage degree, especially at early and hidden damage stages. Considering the dispersion of MMM data, the K_（vs） statistical law is investigated, which shows that K_（vs） obeys Gaussian distribution. So K_（vs） is the suitable MMM parameter to establish reliability model of welded joints. At last, the original quantitative MMM reliability model is first presented based on the improved stress strength interference theory. It is shown that the reliability degree R gradually decreases with the decreasing of the residual life ratio T, and the maximal error between prediction reliability degree R_1 and verification reliability degree R_2 is 9.15%. This presented method provides a novel tool of reliability testing and evaluating in practical engineering for welded joints.

Modeling the keyhole shape and dimension in plasma arc welding

It is of great significance to model the keyhole shape and dimensions to optimize the plasma arc welding process parameters. In this study, through employing a combined volumetric heat source mode, the weld pool in keyhole plasma arc welding is determined firstly, and then the dynamic force-balance condition on the interface between the plasma jet and the molten metal is dealt with in describing the keyhole formation inside the weld pool. The effects of welding current on the shape and size of keyhole are numerically analyzed. The sharp transformation from a partial keyhole to a full-penetration keyhole is quantitatively demonstrated.

Constitutive Model of Friction Stir Weld with Consideration of its Inhomogeneous Mechanical Properties

In practical engineering, finite element（FE） modeling for weld seam is commonly simplified by neglecting its inhomogeneous mechanical properties. This will cause a significant loss in accuracy of FE forming analysis, in particular, for friction stir welded（FSW） blanks due to the large width and good formability of its weld seam. The inhomogeneous mechanical properties across weld seam need to be well characterized for an accurate FE analysis. Based on a similar AA5182 FSW blank, the metallographic observation and micro-Vickers hardness analysis upon the weld cross-section are performed to identify the interfaces of different sub-zones, i.e., heat affected zone（HAZ）, thermal-mechanically affected zone（TMAZ） and weld nugget（WN）. Based on the rule of mixture and hardness distribution, a constitutive model is established for each sub-zone to characterize the inhomogeneous mechanical properties across the weld seam. Uniaxial tensile tests of the AA5182 FSW blank are performed with the aid of digital image correlation（DIC） techniques. Experimental local stress-strain curves are obtained for different weld sub-zones. The experimental results show good agreement with those derived from the constitutive models, which demonstrates the feasibility and accuracy of these models. The proposed research gives an accurate characterization of inhomogeneous mechanical properties across the weld seam produced by FSW, which provides solutions for improving the FE simulation accuracy of FSW sheet forming.

ANN Based Predictive Modelling of Weld Shape and Dimensions in Laser Welding of Galvanized Steel in Butt Joint Configurations

The quality assessment and prediction becomes one of the most critical requirements for improving reliability, efficiency and safety of laser welding. Accurate and efficient model to perform non-destructive quality estimation is an essential part of this assessment. This paper presents a structured and comprehensive approach developed to design an effective artificial neural network based model for weld bead geometry prediction and control in laser welding of galvanized steel in butt joint configurations. The proposed approach examines laser welding parameters and conditions known to have an influence on geometric characteristics of the welds and builds a weld quality prediction model step by step. The modelling procedure begins by examining, through structured experimental investigations and exhaustive 3D modelling and simulation efforts, the direct and the interaction effects of laser welding parameters such as laser power, welding speed, fibre diameter and gap, on the weld bead geometry (i.e. depth of penetration and bead width). Using these results and various statistical tools, various neural network based prediction models are developed and evaluated. The results demonstrate that the proposed approach can effectively lead to a consistent model able to accurately and reliably provide an appropriate prediction of weld bead geometry under variable welding conditions.

Effects of modeling means on properties of monitoring models of spot welding quality

Analyzing and modeling the relation between monitoring information during welding and quality information of the joints is the foundation of monitoring resistance spot welding quality. According to the means of modeling, the known models can be divided into three large categories: single linear regression models, multiple linear regression models and multiple non linear models. By modeling the relations between dynamic resistance information and welding quality parameters with different means, this paper analyzes effects of modeling means on performances of monitoring models of resistance spot welding quality. From the test results, the following conclusions can be drawn: By comparison with two other kinds of models, artificial neural network (ANN) model can describe non linear and high coupling relationship between monitoring information and quality information more reasonably, improve performance of monitoring model remarkably, and make the estimated values of welding quality parameters more accurate and reliable.

MODEL OF LASER-TIG HYBRID WELDING HEAT SOURCE

The welding mechanism of laser-TIG hybrid welding process is analyzed. Withthe variation of arc current, the welding process is divided into two patterns: deep-penetrationwelding and heat conductive welding. The heat flow model of hybrid welding is presented. As todeep-penetration welding, the heat source includes a surface heat flux and a volume heat flux. Theheat source of heat conductive welding is composed of two Gaussian distribute surface heat sources.With this heat source model, a temperature field is calculated. The finite element code MARC isemployed for this purpose. The calculation results show a good agreement with the experimental data.

Prediction of Weld Joint Shape and Dimensions in Laser Welding Using a 3D Modeling and Experimental Validation

This paper presents an experimentally validated weld joint shape and dimensions predictive 3D modeling for low carbon galvanized steel in butt-joint configurations. The proposed modelling approach is based on metallurgical transformations using temperature dependent material properties and the enthalpy method. Conduction and keyhole modes welding are investigated using surface and volumetric heat sources, respectively. Transition between the heat sources is carried out according to the power density and interaction time. Simulations are carried out using 3D finite element model on commercial software. The simulation results of the weld shape and dimensions are validated using a structured experimental investigation based on Taguchi method. Experimental validation conducted on a 3 kW Nd: YAG laser source reveals that the modelling approach can provide not only a consistent and accurate prediction of the weld characteristics under variable welding parameters and conditions but also a comprehensive and quantitative analysis of process parameters effects. The results show great concordance between predicted and measured values for the weld joint shape and dimensions.

Modeling of welded bead profile for rapid prototyping by robotic MAG welding

As a deposition technology, robotic metal active gas （MAG） welding has shown new promise for rapid prototyping （ RP） of metallic parts. During the process of metal forming using robotic MAG welding, sectional profile of single-puss welded bead is critical to formed accuracy and quality of metal pans. In this paper, the experiments of single-pass welded bead for rapid prototyping using robotic MAG welding were carried out. The effect of some edge detectors on the cross-sectional edge of welded bead was discussed and curve fitting was applied using least square fitting. Consequently, the mathematical model of welded bead profile was developed. The experimental results show that good shape could be obtained under suitable welding parameters. Canny operator is suitable to edge detection of welded bead profile, and the mathematical model of welded bead profile developed is approximately parabola.

Analytical Modelling of Shot-peening Residual Stress on Welding Carbon Steel Surface Layer

The residual stress distribution was studied by an analytical model, due to shot peening on the welding carbon steel surface layer. The initial welding residual stresses before shot peening were taken into consideration in this analytical model. The Hertzian elastic contact theory was used to get the elastic compression stress state after impact on the surface layer. The initial welding stress field and the shot peening stress field would superpose and the welding surface layer would yield based on the elastic-plastic evaluation, then the residual stress after shot peening can be achieved. The influence of initial welding residual stress on the stress distribution after shot peening was analyzed and discussed. A series of experiments were carried out and the residual stress on the welding surface was determined by X-ray diffractometer before and after shot peening. The calculation results of the analytical model are consistent with the experimental results. The critical shot velocities when welding surface layer yielded and reverse yielded were calculated. While the welded joint surface material reversely yielded, the maximum compressive residual stress would not obviously increase with the increase of shot velocity, the thickness of the compressive stress layer would be increased. Welding residual tensile stress can enlarge the thickness of the compressive stress layer at the same shot velocity when reverse yield appeared.

Analytical Solution for Model-Based Dynamic Power Factor Measurement in AC Resistance Spot Welding

On the basis of welding transformer circuit model, a new measuring method was proposed. This method measures the peak angle of the welding current, and then calculates the dynamic power factor in each half-wave. An artificial neural network is trained and used to generate simulation data for the analytical solution, i.e. a high-order binary polynomial, which can be easily adopted to calculate the power factor online. The tailored sensing and computing system ensures that the method possesses a real-time computational capacity and satisfying accuracy. A DSP-based resistance spot welding monitoring system was developed to perform ANN computation. The experimental results suggest that this measuring method is feasible.

Modelling of the plasma-MIG welding temperature field

A three-dimensional simulation model for the plasma-MIG welding process, which takes the interaction between the plasma arc and MIG arc into account, is presented and the quasi-steady temperature fields on the workpiece are calculated with the model. The 10 mm-5A06 aluminum alloy is welded and the temperature fields are measured with the thermoelectric couple. The simulation results and measured results show that the biggest deviation of peak temperature between them is below 20 ℃, which indicates good coincidence between the simulation and measurement.

Modeling of Arc Force in Plasma Arc Welding

A three-dimensional mathematical model for the transferred-type argon arc was devel- oped to describe arc force on the anode surface. The software ANSYS was employed to solve the model. The model includes a part of torch and tungsten electrode to achieve more reasonable results. The arc temperature and flow fields were derived. And the influences of welding parameters on arc force were also studied. The simulated results show that arc pressure at the anode are dependent on the welding current, plasma gas flow rate and electrode neck-in, while not sensitive to arc length.

A new simulation model and its application in CO_2 short-circuiting transfer welding

A new simulation model of CO 2 short circuiting transfer welding may be employed to develop a new pattern of welding machine and to predict welding process parameters to obtain the optimum welding technology properties. In this paper, a new simulating model is developed according to the AWP (adapting welding physics process) waveform control method. Good agreement is shown between the predicted and experimentally determined results. The model will make an important promotion in the development of CO 2 arc welding technique.

Artificial neural networks applied to spot welding process modeling

Artificial neural networks have been studied for applicability for modeling of spot welding process. Some basic concepts relating to neural networks are explained as well as how they can be used to model welding qualitv parameters in terms of the welding process parameter. The performance of the neural networks for modeling is presented and evaluated using actual welding data. It is concluded that neural network modeling is a good means of estimating spot welding quality on-line.

Weldability evaluation and tensile strength estimation model for aluminum alloy lap joint welding using hybrid system with laser and scanner head

Aluminum welding using a hybrid system with a laser and scanner welding head was performed under various welding conditions to verify the feasibility of applying an aluminum alloy to a car body.The experimental material was 5J32 aluminum alloy,and the laser power,welding speed,and laser incidence angle were used as the control variables.The weld bead shape and the tensile shear strength were evaluated in order to understand the aluminum lap joint weld characteristics.Analysis of variance (ANOVA) was conducted to identify the effect of the process variables on the tensile shear strength.Tensile strength estimation models using three different regression models were also suggested.The input variables were the laser power,welding speed,and laser incidence angle,and the output was the tensile shear strength.Among the models,the second-order polynomial estimation model had the best estimation performance,and the average error rate of this model was 0.058.

Petri net based modeling and analysis for weldingflexible manufacturing cell

Due to the development of advanced manufacturing technology and the introduction of Smart Manufacturing notion in the field of modern industrial production, welding flexible manufacturing using robot technology has become the inevitable developing direction on welding automation. Based on a new intelligent arc welding flexible manufacturing cell (WFMC), its system structure and control policies are studied in this paper. Aiming at the different information flows among every subsystem and central monitoring computer in this WFMC, Petri net theory is introduced into the process of welding manufacturing. A discrete control model of WFMC has been constructed, in which the system's status is regarded as place and the control process is regarded as transition. Moreover, grounded on automation Petri net principle, the judging and utilizing of information obtained from welding sensors are imported into Petri net structure, which extends the traditional Petri net concepts. The control model and policies researched in this paper have established foundation for further intelligent real time control on welding flexible manufacturing cell and system.

Modeling and simulating of unloading welding transformer

The simulation model of an unloading welding transformer was established on the basis of MATLAB software, and the modeling principle was described in detail in the paper. The model was made up of three sub models, i.e. the linear inductor sub model, the non linear inductor sub model and series connection sub model controlled by current, and these sub models were jointed together by means of segmented linearization. The simulating results showed that, in the conditions of the high convert frequency and the large cross section of the magnet core of a welding transformer, the non linear inductor sub model can be substituted by a linear inductor sub model in the model; and the leakage reactance in the welding transformer is one of the main reasons of producing over current and over voltage in the inverter. The simulation results demonstrate that the over voltage produced by leakage reactance is nearly two times of the input voltage supplied to the transformer, and the lasting time of over voltage depends on time constant τ 1. With reducing of τ 1, the amplitude of the over current will increase, and the lasting time becomes shorter. Contrarily, with increasing of τ 1, the amplitude of the over current will decrease, and the lasting time becomes longer. The model has played the important role for the development of the inverter resistance welding machine.