再制造HT250基体的亚激光瞬间熔技术工艺参数优化

工艺参数的选取对再制造产品的表面质量至关重要。采用亚激光瞬间熔技术修复了HT250基体的表面缺陷,并利用响应曲面法(RSM)和有限单元法(FEM)对其修复过程的工艺参数进行了优化。同时详细分析了输入功率P、单次修复时间t、速度V和保护气体流量G等4个因素对修复后试样抗拉强度的影响。研究结果表明:抗拉强度受输入功率和单次修复时间影响显著,而对其它元素呈弱依赖性。HT250基体的亚激光瞬间熔技术的最优工艺参数为输入功率2 800 W,持续时间0.57s,速度6.5mm/s,气体流量3L/min。     

激光熔覆镍基熔覆层截面形貌预测

利用BP神经网络建立激光熔覆关键工艺参数(激光功率、扫描速度、送粉电压、送粉载气流量)与熔覆层截面形貌(熔宽、余高)的预测模型。以激光熔覆工艺参数为输入,熔覆层的截面形貌为输出,利用工艺试验数据对网络进行训练,实现对输入和输出的高度映射。结果表明,BP神经网络可以较好地对熔覆层形貌进行预测,同时双隐藏层BP神经网络模型预测结果误差波动更小,表现出优良的稳定性,最大预测误差相比单隐藏层神经网络大大降低。     

Al-5Mg-0.3Sc激光焊接技术

针对铝合金材料传统焊接工艺的缺点,提出了铝合金材料的激光焊接修复工艺.通过对Al-Mg-0.3Sc激光对焊焊缝的金相组织分析、抗拉强度和显微硬度测试,研究了如何有效控制CO2连续激光器的工艺参数,提高焊缝的质量.结果表明,在优化激光功率、激光扫描速度、保护气体流量等焊接工艺参数的前提下,由于稀土元素Sc的作用,焊缝中心的晶粒仅为基体的1/10,抗拉强度达到了基体的88%,显微硬度达到了基体的95%,焊缝无气孔和裂纹缺陷.     

基于蚁群算法的激光表面淬火工艺参数神经网络优化系统

建立了基于蚁群算法的激光表面淬火工艺参数神经网络优化系统。用神经网络建立激光表面淬火工艺参数与目标参数的非线性模型,借助蚁群算法搜索决策工艺参数的最优组合,自动优化工艺参数。用VC++6.0开发了激光表面淬火工艺参数优化程序。结果表明,基于蚁群算法的神经网络优化系统用于解决激光表面淬火工艺参数优化问题是可行且有效的。     

激光熔覆修复青铜零件的实验研究和工程应用

青铜具有极好的耐海水腐蚀性和耐磨损性能,在舰艇、船舶中大量存在青铜零件,但对这些零件进行修复非常困难。由于青铜对激光的强烈反射及其优良的热传导性,给激光熔覆修复青铜零件带来了很大的困难。通过激光熔覆修复实验,优化了激光熔覆修复工艺参数。在对激光熔覆修复过程进行最优控制的条件下,获得了界面结合良好、耐腐蚀性和耐磨损性均符合要求的激光熔覆修复试样。在此基础上,实现了对实际舰船青铜零件的激光熔覆修复。     

金属构件激光熔覆强化的研究

以45钢作为基体材料,对激光熔覆工艺参数中的激光熔覆功率、扫描速度对熔覆层质量的影响进行了探讨,并得出最佳的激光熔覆工艺参数。对试件进行了激光熔覆修复实验,修复后试件的表面硬度、耐磨性、耐腐蚀等性能得到明显提高。     

随机森林回归分析在激光熔覆形貌预测中的应用

激光熔覆修复过程中单道熔覆层形貌极大地影响修复效果,但多工艺参数对熔覆层影响的耦合作用机制尚未被研究清楚,因此,获得不同工艺参数组合与熔覆层尺寸的定量关系是亟待解决的难题。以Inconel 625合金的激光熔覆修复为背景,采用随机森林(Random Forest,RF)算法构建了激光熔覆工艺参数(激光功率、扫描速度、送粉速率)到单道熔覆层尺寸的回归模型,将模型用于特定熔覆参数组下单道尺寸的预测;同时在给定期望的单道熔覆层尺寸参数时,基于Gini不纯度选择强关联因子构建了工艺参数预测模型。结果表明,激光熔覆工艺参数预测模型的预测误差小于4%,能够准确地估计加工特定单道熔覆层截面几何形状所需的激光熔覆工艺参数。     

高速动车组EA4T车轴激光增材修复研究

为验证激光增材修复技术在高速动车组车轴损伤修复应用中的可行性,在车轴基材上开展了激光修复工艺试验,重点研究激光功率和扫描速度对熔覆质量的影响,通过分析研究不同激光功率、扫描速度下所得试样的宏观熔覆形貌、宏观金相分析、显微硬度、金相组织等,筛选出较优的工艺参数,并进一步对熔覆试样的拉伸性能、冲击性能、应力腐蚀及疲劳试验等多项力学性能检测。结果表明,采用优化后的工艺参数在EA4T上激光熔覆IN625镍基粉末,其熔覆试样拉伸性能优于母材标准要求,冲击性能优于基材的冲击性能,疲劳寿命与基材相当,达到了车轴服役性能的要求,可用于后续高速动车组EA4T车轴上的修复。     

16Mn钢表面激光熔覆Ni60合金关键参数优化

采用ANSYS有限元软件对16Mn钢表面激光熔覆Ni60合金过程中的温度场进行数值模拟,分析激光熔覆工艺参数对温度场的影响,并以保证熔覆层质量的前提下,使基体表面得到较深的硬化层为目标,对激光功率和扫描速度两个工艺参数进行优化设计,得到了最佳熔覆参数;激光熔覆实验研究发现,优化后的工艺参数较为合理,实验结果也证实了数值优化结果的可靠性。     

基于PSO-BP算法的3D打印制件精度预测模型

针对选择性激光烧结(SLS)中制件精度和工艺参数难以选择的问题以及BP神经网络本身缺陷,提出一种利用粒子群算法优化的BP神经网络建立SLS烧结件精度预测模型的方法。首先根据SLS成型工艺的特点,分析影响成型件精度的因素,通过实验获得不同激光功率、扫描速度、扫描间距和分层厚度条件下多组成型件精度数据,并采用多目标函数优化的单目标化思想优化目标函数,然后通过粒子群算法优化BP神经网络。用优化后的最优解作为BP神经网络算法的初始权值和阈值,利用MATLAB建立优化后的BP神经网络预测模型,对优化后的精度函数模型进行预测分析,并与传统BP神经网络获得的预测结果进行对比。结果表明:粒子群优化的神经网络模型具有良好的全局搜索能力和收敛性,精度预测更加准确,对SLS打印制件具有一定的指导作用。     

A Comparative Study of Artificial Neural Network and Response Surface Methodology for Optimization of Friction Welding of Incoloy 800 H

This article deals with the optimization of process parameters for friction welding of Incoloy 800 H rod and compares the results obtained by response surface methodology(RSM) and artificial neural network(ANN).The experiments were carried out on the basis of a five-level,four-variable central composite design.The output parameters were the tensile strength and burn-off length(BOL).They were considered as a function of four independent input variables,namely heating pressure(HP),heating time,upsetting pressure(UP),and upsetting time.The RSM results showed that the quadratic polynomial model depicted the interconnection between individual element and response.For optimizing the process parameters,ANN analysis was used,and the optimal configuration of the ANN model was found to be 4–9–2.For modeling aspect,a requisite trained multilayer perceptron neural network was rooted,and a quick propagation training algorithm was used to train ANN.The purpose of optimization was to decide the maximum tensile strength and minimum burn-off length of the welded joint which was done by varying the friction welding process variables.The order of importance of input parameters for friction welding of Incoloy 800 H was HP [ UP [ N [ BOL.After predicting the model using RSM and ANN,a comparison was made for predicting the effectiveness of two methodologies.By analyzing the results,it was observed that as compared to RSM,ANN model was more specific.     

激光选区熔化TC4合金工艺优化及退火处理对显微组织的影响研究

激光选区熔化技术是制备复杂钛结构的重要加工方式,而热处理是必要的后处理手段.首先利用激光选区熔化设备打印TC4合金块体结构,以激光功率、扫描速度及扫描间距为优化对象,以致密度为优化目标开展正交试验,得到成形工艺参数对致密度的影响排序及最优工艺参数.然后对最优工艺参数下的成形样件分别进行消除应力退火处理与完全退火处理,发...     

Effect of Rotation Rate on Microstructure and Mechanical Properties of Friction Stir Processed Ni-Fe-Based Superalloy

In this work,friction stir processing (FSP) was applied to the high-strength and high-melting-point Ni-Fe-based superal-loy (HT700) for the first time with negligible wear of the stir tool.Different rotation rates were chosen to investigate the effect of heat input on microstructure and tensile properties at different temperatures of friction stir processed Ni-Fe-based superalloy.The results showed that with increasing rotation rate,the percentage of high-angle grain boundaries and twin boundaries gradually decreased whereas the grain size initially increased and then remained almost constant;the difference in tensile properties of FSP samples with rotation rates of 500-700 rpm was small attributing to their similar grain size,but the maximum strength was achieved in the FSP sample with a rotation rate of 400 rpm and traverse speed of 50 mm/min due to its finest grain size.More importantly,we found that the yield strength of all FSP samples tensioned at 700 ℃ was enhanced clearly resulting from the reprecipitation of γ'phase.In addition,the grain refinement mechanism of HT700 alloy during FSP was proved to be continuous dynamic recrystallization and the specific refinement process was given.     

基于响应面法的不锈钢车体激光焊接工艺参数优化

为解决电阻点焊不锈钢车体表面质量差、密闭性差等问题,采用二次回归旋转设计试验方案,基于响应面法建立了不锈钢车体激光焊接工艺参数(激光功率、焊接速度、离焦量)与预测响应值(熔深、熔宽、接头剪切拉伸载荷)之间的数学模型,能够根据车体表面质量和接头强度的要求优选焊接工艺参数.并通过优化激光焊接工艺参数来预测激光搭接焊接头的熔深、熔宽以及接头的剪切拉伸载荷,实现焊缝成形与接头强度的最佳组合,为改善不锈钢车体焊接表面质量提供了新的工艺途径.     

基于工艺参数的7005铝合金力学性能的支持向量回归预测

根据7005铝合金在不同工艺参数(挤压温度、挤压速度、淬火方式和时效条件)下的力学性能(抗拉强度σ_b、屈服强度σ_(0.2)和硬度HB)实测数据集,应用基于粒子群算法(PSO)寻优的支持向量回归(SVR)结合留一交叉验证(LOOCV)的方法,对7005铝合金力学性能进行建模和预测研究,并与偏最小二乘法(PLS)、反向传播人工神经网络(BPNN)和两者结合的PLS-BPNN模型的预测结果进行比较.结果表明:基于SVR-LOOCV法的预测精度最高,对3种力学性能(σ_b、σ_(0.2)和HB)预测的均方根误差(RMSE)分别为4.531 9 MPa、14.550 8 MPa和HB1.414 2,其平均相对误差(MRE)分别为0.72%、2.61%和0.66%,均比PLS、BPNN和PLS-BPNN方法预测的RMSE和MRE要小.     

Intelligent modeling and optimization on time-sharing power dispatching system for electrolytic zinc process

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预制坡口角度对激光增材再制造IN718合金组织与性能的影响

目的研究在激光增材再制造IN718合金过程中,不同预制坡口角度对其组织与性能的影响。方法利用激光增材再制造技术对不同预制凹槽进行逐层叠加修复,采用光学显微镜观察显微组织,采用扫描电镜观察断口形貌,采用维氏硬度计对再制造试样进行硬度测量,采用残余应力测试仪测量再制造后基体表面的残余应力,采用万能拉伸试验机进行拉伸力学性能测试。结果当预制坡口角度大于130°时,能得到无组织缺陷、成形质量良好的增材再制造试样;当预制坡口角度小于110°时,修复界面会出现熔合不良现象,且修复区内部会出现裂纹。预制大的坡口角度进行激光增材再制造试验能获得组织更加细密、硬度分布更为均匀的再制造层,且大的坡口角度能有效降低再制造试样基体的残余应力。增大坡口角度有助于提高再制造试样的塑性,随着坡口角度的减小,再制造试样的力学性能变差。结论在进行激光增材再制造试验时,不宜预制过小的坡口角度,应根据损伤情况预制坡口角度较大的凹槽,有助于增加再制造成形件的组织均匀性,提高其力学性能。     

AZ31B镁合金的脉冲电流气体保护钨极焊过程参数优化(英文)

建立预测脉冲电流气体保护钨极焊AZ31B镁合金接头的拉伸强度经验方程。研究焊接过程参数如峰值电流、基础电流、脉冲频率和脉冲时间对焊接接头的影响。试验设计了一个四因素五水平的正交实验。建立的经验方程能够有效地预测脉冲电流钨电极惰性气体保护焊AZ31B镁合金的焊缝拉伸强度,可信度为95%。结果表明,脉冲频率对拉伸强度的影响最大,其次是峰值电流、脉冲时间和基电流。     

Multiobjective Optimization of Atmospheric Plasma Spray Process Parameters to Deposit Yttria-Stabilized Zirconia Coatings Using Response Surface Methodology

Atmospheric plasma spraying is used extensively to make Thermal Barrier Coatings of 7-8% yttria-stabilized zirconia powders. The main problem faced in the manufacture of yttria-stabilized zirconia coatings by the atmospheric plasma spraying process is the selection of the optimum combination of input variables for achieving the required qualities of coating. This problem can be solved by the development of empirical relationships between the process parameters (input power, primary gas flow rate, stand-off distance, powder feed rate, and carrier gas flow rate) and the coating quality characteristics (deposition efficiency, tensile bond strength, lap shear bond strength, porosity, and hardness) through effective and strategic planning and the execution of experiments by response surface methodology. This article highlights the use of response surface methodology by designing a five-factor five-level central composite rotatable design matrix with full replication for planning, conduction, execution, and development of empirical relationships. Further, response surface methodology was used for the selection of optimum process parameters to achieve desired quality of yttria-stabilized zirconia coating deposits.