自保护药芯焊丝焊接工艺参数的敏感性分析

自保护药芯焊丝是一种适合于野外作业的焊接材料,广泛应用于船舶、钻井平台、石油管道、集装箱等结构件焊接及修复. 采用自保护药芯焊丝在Q235钢板表面进行单层单道平板堆焊试验,运用二次回归通用旋转组合设计方法建立了电弧电压、送丝速度、焊接速度与熔宽、余高、熔高的二次回归数学模型,分析了工艺参数与熔敷几何尺寸的关系. 结果表明,该模型能够预测稳定工艺区间内工艺参数变化对熔敷层几何尺寸的影响规律;当电压较低时,送丝速度是影响熔宽和余高的主要因素,电压较高时,焊接速度是影响熔宽和余高的主要因素.     

焊接参数对铝合金VPPA焊缝成形的影响

在铝合金变极性等离子弧穿孔立焊过程中,正、反极性电流和离子气流量等焊接参数对焊缝成形和焊缝质量都有显著影响,这些焊接参数的合理匹配是保证穿孔过程和焊缝稳定成形的重要前提.试验采用厚度10 mm的LD10铝合金板作为焊接母材,重点研究了焊接电流和离子气流量对焊缝质量的影响,分析了正、反极性电流的幅值和时间比对焊缝成形的影响规律.研究结果表明:随着焊接电流的增大,焊缝背面熔宽和余高增大,正面熔宽增大而余高减小;随着离子气流量的增大,焊缝背面余高和宽度增加,正面余高和宽度减小.     

窄坡口等离子-MAG复合焊工艺参数优化

针对转向架构架焊接变形及根部焊道背部成形问题,研究坡口角度为30°的V形窄坡口旁轴式等离子-MAG复合热源焊接工艺.文中以SMA490BW耐候钢平板对接为研究对象,基于响应面法建立了主要影响熔深的等离子电流、MAG电流、焊接速度、等离子气体流量与焊缝根部焊道的熔深、背部余高之间的数学关系模型,并依此模型分析了等离子-MAG复合焊接工艺参数对焊缝熔深能力的影响,获得了合适的复合焊接工艺参数.与普通MAG焊相比,窄坡口等离子-MAG复合焊接工艺既可保证焊缝根部完全熔透又能有效地减小接头的焊接变形.     

激光/等离子电弧复合热源能量参数对钛合金焊缝成形的影响

在对钛合金激光/等离子电弧复合焊与单一激光焊的焊缝成形进行比较的基础上,研究了激光在复合等离子电弧后主要焊接工艺参数对焊缝成形的影响.结果表明,随激光功率增大和焊接速度降低,复合焊与单一激光焊焊缝的横截面形貌均由钉形向近X形转变.与单一激光焊相比,复合焊焊缝的余高和咬边较大.激光/等离子电弧"协同效应"随激光功率和焊接速度变化而不同,从而影响复合焊焊缝的熔宽和熔宽比.随焊接电流从零增大到60 A,焊缝熔宽略有增大,而焊缝熔宽比基本保持不变.     

机器人MAG焊工艺参数对焊缝成形的影响

采用机器人MAG焊方法进行平敷焊焊接试验,研究机器人MAG焊金属快速成形过程中重要焊接工艺参数对焊缝成形的影响。采用单因素试验方法,分别试验焊接电流、焊接电压、焊接速度、干伸长对焊缝成形的影响,获得了各不同工艺参数对焊缝几何尺寸(焊缝宽度、余高、熔深)的影响规律。试验结果表明,焊接电流、焊接电压、焊接速度对焊缝几何尺寸的影响显著,干伸长对焊缝几何尺寸的影响较小。通过改变各工艺参数可对焊缝几何尺寸进行微调。     

焊接成形中焊接参数的选取与焊缝尺寸的预测

通过TIG堆焊试验,获取了在一定焊接参数下成形焊缝的熔宽、余高尺寸数据.建立了双BP神经网络模型:模型1,由焊接参数预测焊缝尺寸;模型2,由焊缝尺寸预测焊接参数.可先通过模型2预测一定尺寸的焊缝所对应的焊接参教,对预测的焊接参数作适当调整后再输入到模型1中,检验该焊接参数条件下获得的焊缝尺寸是否符合要求.可以利用此双模型选取合适的焊接参数来对焊缝尺寸进行控制,取得了较好的试验效果.     

旁轴送粉式激光扫描熔覆工艺研究

以Q235钢为基板,采用IPGYLS-4000型光纤激光器以及旁轴送粉器,搭建旁轴同步送粉式激光扫描熔覆工艺试验平台,在基板上进行熔覆试验。研究了激光功率、扫描速度和扫描宽度对熔覆层成形尺寸和对熔覆层组织的影响,结果表明:随着激光功率增大,铁基合金粉末熔化量提高,单层金属熔覆层的余高增加;扫描速度对熔覆层熔宽和余高的影响均较大,随着扫描速度的降低,金属熔覆层熔宽余高均增加,裂纹数量增多。约束应力是导致熔覆层出现裂纹的主要原因,通过优选工艺参数可以获得工艺良好无裂纹熔覆层,为下一步研究激光扫描多层熔覆无(小)变形焊接技术提供理论和技术依据。     

水下湿法焊缝成形的响应曲面法建模及分析

水下湿法焊缝成形是影响水下焊接接头力学性能的重要因素.与空气中焊接相比,影响水下湿法焊缝成形的因素更复杂.在高压舱内进行不同水深湿法药芯焊丝焊接(FCAW)试验,通过响应曲面法(RSM)分别建立水下湿法焊缝的熔宽和余高与焊接参数之间的数学模型,分析了焊接电流、电弧电压和水深及其交互作用对水下湿法焊缝成形的影响.结果表明,水下湿法焊接时增大焊接电流和电弧电压都可以增大焊缝熔宽.熔宽随着水深的增大而减小,但随着水深的增大,水深对减小熔宽的作用逐渐减小.随着电流的增大,焊缝余高增大,且比电弧电压对余高的作用明显.     

基于神经网络模型的CMT脉冲焊接焊缝几何形状预测

为了研究冷金属过渡(CMT)脉冲焊接过程中工艺参数对熔透、焊缝熔宽和焊缝余高的影响,提出了一种用于预测焊缝几何形状(焊缝高度和宽度)和熔透状态(深度和面积)的反向传播神经网络模型。该模型以峰值焊接电流,焊接速度和热量输入作为输入参数,且以焊缝高度和宽度、熔深和稀释面积作为输出参数,并给出了设计框架。结果表明,神经网络与训练数据有很好的一致性,可以有效地用于焊缝和熔透几何参数的预估。预测值与实验值之间的误差百分比较小,验证了提出模型的有效性。     

成形参数和搭接量对堆焊成形尺寸的影响

为了分析不同工艺参数对堆焊成形尺寸的影响并确定其最优参数组合,在前期研究的基础上,选取与堆焊成形质量密切相关的3个主要工艺参数,即焊接速度、送丝速度和焊接电压,通过正交试验法设计了焊接试验,并采用极差分析法对试验结果进行了分析。结果表明:焊接速度对焊道熔宽影响最大,而送丝速度对焊道余高影响最大,得到最优参数组合为焊接速度4 mm/s,送丝速度80 mm/s,焊接电压20 V。在此基础上,研究了其焊道搭接量模型,确定出两道焊道之间的最佳搭接距离,通过试验验证了搭接模型的可靠性,最后得到的多道堆焊零件表面平整度较好。     

基于支持向量机的焊缝尺寸预测

焊缝尺寸是决定焊接接头强度及有关性能的重要因素,因此也是焊接质量控制的重要内容.分别以焊接电流、电弧电压以及焊接速度作为输入向量构造样本集,建立CO2焊接焊缝尺寸支持向量机模型,分别运用线性核函数,多项式核函数、高斯径向基核函数以及指数径向基核函数对焊缝熔宽、焊缝熔深以及焊缝余高进行预测.结果表明,采用指数径向基核函数所建立的支持向量机模型可以有效地对焊缝尺寸进行预测,为进一步实现焊缝质量的在线控制提供依据.     

Prediction of bead geometry in pulsed GMA welding using back propagation neural network

This paper presents the development of a back propagation neural network model for the prediction of weld bead geometry in pulsed gas metal arc welding process. The model is based on experimental data. The thickness of the plate, pulse frequency, wire feed rate, wire feed rate/travel speed ratio, and peak current have been considered as the input parameters and the bead penetration depth and the convexity index of the bead as output parameters to develop the model. The developed model is then compared with experimental results and it is found that the results obtained from neural network model are accurate in predicting the weld bead geometry.     

基于多因素权重法的高压GMAW焊缝成形分析

水下高压干式GMAW焊缝成形难以控制,影响焊接质量,通过多因素权重法对影响高压GMAW焊缝成形的参数进行分析,以确定焊接过程中主要参数与焊缝成形之间的关系. 以高压GMAW焊接正交试验结果作为训练样本,利用BP神经网络建立了焊缝成形预测模型. 将模型预测结果与实际焊接试验结果进行对比,验证了模型的精确度. 以预测模型中的权值为基础,通过Garson算法得出各参数变量对于焊缝成形参数的权重系数,并通过高压干式GMAW试验进行验证. 结果表明,不同焊接参数变化引起的焊缝成形参数变化幅度与相应焊接参数对焊缝成形的影响权重基本对应,所得权重系数对于高压GMAW焊接工程应用具有指导作用.     

Sensitivity analysis for process parameters in GMA welding processes using a factorial design method

Generally, the quality of a weld joint is strongly influenced by process parameters during the welding process. In order to achieve high quality welds, mathematical models that can predict the bead geometry and shape to accomplish the desired mechanical properties of the weldment should be developed. This paper focuses on the development of mathematical models for the selection of process parameters and the prediction of bead geometry (bead width, bead height and penetration) in robotic GMA (Gas Metal Arc) welding. Factorial design can be employed as a guide for optimization of process parameters. Three factors were incorporated into the factorial model: arc current, welding voltage and welding speed. A sensitivity analysis has been conducted and compared the relative impact of three process parameters on bead geometry in order to verify the measurement errors on the values of the uncertainty in estimated parameters. The results obtained show that developed mathematical models can be applied to estimate the effectiveness of process parameters for a given bead geometry, and a change of process parameters affects the bead width and bead height more strongly than penetration relatively.     

Artificial neural network approach for estimating weld bead width and depth of penetration from infrared thermal image of weld pool

Abstract

In this article an artificial neural network based system to predict weld bead geometry using features derived from the infrared thermal video of a welding process is proposed. The multilayer perceptron and radial basis function networks are used in the prediction model and an online feature selection technique prioritises the features used in the prediction model. The efficacy of the system is demonstrated with a number of welding experiments and using the leave one out cross-validation experiments.     

Fuzzy Regression Model to Predict the Bead Geometry in the Robotic Welding Process

Recently, there has been a rapid development in computer technology, which has in turn led to develop the fully robotic welding system using artificial intelligence (AI) technology. However, the robotic welding system has not been achieved due to difficulties of the mathematical model and sensor technologies. The possibilities of the fuzzy regression method to predict the bead geometry, such as bead width, bead height, bead penetration and bead area in the robotic GMA (gas metal arc) welding process is presented. The approach, a well-known method to deal with the problems with a high degree of fuzziness, is used to build the relationship between four process variables and the four quality characteristics, respectively. Using these models, the proper prediction of the process variables for obtaining the optimal bead geometry can be determined.     

Formability consideration during bead optimisation to stiffen deep drawn parts

Beads that alter the geometry of sheet parts can increase the stiffness of deep drawn sheet parts. The locations and geometry of the beads have a great influence on the stiffness of the parts. The design of beads is the result of numerous bead optimisations, developed without considering the manufacturability. Therefore, a bead optimisation algorithm should be developed to increase the efficiency of the bead design while simultaneously considering manufacturability. The trajectory generated along the principal direction of bending stress determines the locations of the beads that maximise the stiffness of the parts. Formability is chosen as a criterion that effectively suggests itself for the initial bead geometry during bead optimisation. The influences of the deep drawing depth, initial specimen geometry and bead height on formability are then investigated by means of a sensitivity analysis. The maximum formable bead height as function of pre-strains is derived from this sensitivity analysis using linear superposition and second order polynomial fitting. The initial bead height function will play a crucial role in supplying the initial values and the validity of the simulation model is experimentally confirmed by the chosen bead locations and geometry.     

Sensitivity analysis of submerged arc welding process parameters

Selection of process parameters has great influence on the quality of a welded connection. Mathematical modelling can be utilized in the optimization and control procedure of parameters. Rather than the well-known effects of main process parameters, this study focuses on the sensitivity analysis of parameters and fine tuning requirements of the parameters for optimum weld bead geometry. Changeable process parameters such as welding current, welding voltage and welding speed are used as design variables. The objective function is formed using width, height and penetration of the weld bead. Experimental part of the study is based on three level factorial design of three process parameters. In order to investigate the effects of input (process) parameters on output parameters, which determine the weld bead geometry, a mathematical model is constructed by using multiple curvilinear regression analysis. After carrying out a sensitivity analysis using developed empirical equations, relative effects of input parameters on output parameters are obtained. Effects of all three design parameters on the bead width and bead height show that even small changes in these parameters play an important role in the quality of welding operation. The results also reveal that the penetration is almost non-sensitive to the variations in voltage and speed.     

薄板TIG堆焊屈曲变形的预测

针对TIG堆焊所引起的薄板复杂屈曲变形问题,采用基于热弹塑性理论的有限元法建立薄板焊接变形预测模型,提出了数字图像相关法对预测屈曲模型进行试验验证并设计了薄板焊接变形检测试验装置. 结果表明,基于数字图像相关技术的非接触变形检测方法能够全场动态获取堆焊屈曲变形数据,全面验证了焊接变形有限元预测模型,基于高斯热源模型、非线性瞬态热传导边界条件、材料高温性能参数等的热?力耦合热弹塑性预测模型具有较高的精度.薄板焊接变形冷却后呈马鞍形,结合动态温度场与应力场,对揭示焊接马鞍形屈曲变形机理具有重要的意义.     

Mixed logical dynamical model for back bead width prediction of pulsed GTAW process with misalignment

The purpose of this paper is to propose a kind of mixed logical dynamical (MLD) model to predict the back bead width of pulsed GTAW process with misalignment. Misalignment is considered as discrete input and the nonlinear welding process is approximated using piecewise linear models. A MLD model is then established and gives a good prediction quality of the back bead width of pulsed GTAW process with misalignment. The stability and reliability of the MLD model are tested by a closed loop control experiment. This study shows that the MLD framework is a good modeling method for pulsed GTAW process. Thus, a solid foundation for penetration control of welding process is established based on the MLD model.