金属选区激光熔化成型设备控制系统设计

根据金属选区激光熔化成型设备的工作原理和控制要求,设计了以MCP控制平台为核心的控制系统。介绍了MCP控制平台的主要接口及其与激光器、振镜和步进电动机等主要执行元件的硬件连接;详细阐述了MCP控制平台主要配置开发过程,给出了激光扫描、铺粉、成型仓环境控制和人机界面(Human Machine Interface,HMI)信息交互等主要工艺的控制方式。经样机生产验证,该控制系统硬件结构简单,基于API函数的脚本开发方便快捷,系统研发周期短,运行稳定,适合工业化应用。     

激光选区熔化成型可控超轻结构化零件的孔隙生成效果

本文主要研究了孔隙率等参数可控的自动超轻结构化金属零件的增材制造。以方块零件及一个具有复杂外形的零件为研究对象,分析了面向激光选区熔化工艺的可控超轻结构化零件的孔隙生成效果,重点探讨了成型工艺对超轻结构化零件孔隙率的影响。结果显示:通过计算机数值计算,可将方块CAD模型快速自动转化为可控超轻结构化模型,计算孔隙率误差可控制在±2%以内;激光深穿透现象会导致带悬垂面内壁的壁厚增加,所引起的孔隙率误差值为负值,且计算孔隙率越大,负值倾向越严重;而成型工艺性不致密导致的孔隙率误差为正值,且在相同工艺条件下,计算孔隙率越大,该误差值越小。故为使总孔隙率误差能较好地反映超轻结构网格孔隙的控制精度,应提高成型时实体部分的致密性。按45%设定孔隙率成功地将具有复杂结构的零件转化为计算孔隙率为44.62%的超轻结构化模型,采用高致密性激光选区熔化工艺成型后,实测孔隙率为42.94%,无悬垂面的内壁壁厚误差≤0.06mm,达到了较好的超轻结构控制效果。     

数字孪生驱动的金属选择性激光熔融成形过程在线监控

由激光熔融过程的极热极冷特性造成的成形零件质量缺陷一直阻碍着选择性激光熔融技术的广泛应用,为制造出高质量的零件,提出一种数字孪生驱动的金属选择性激光熔融成形过程在线监控方法,应用该方法建立智能成形系统并进行案例分析.基于粉末熔融过程的物理和虚拟建模、过程在线监测和大数据分析,构建了包括设备层、数据转换层、网络层、控制层...     

变能量激光选区熔化IN718镍基超合金的成形工艺及高温机械性能

开展了基于激光选区熔化技术对IN718镍基超合金直接激光熔化成形的研究。将零件分为心部与轮廓区,通过改变激光线输入量进行选区熔化研究。首先,建立熔池内烧结的数值模型,改变激光线输入量,获得了激光线输入量对零件致密度的影响规律并观察了成形体中的组织生长。然后,增加轮廓部位扫描,改变激光线输入量与扫描顺序,获得其对零件表面质量的影响规律。最后,通过优化热处理工艺提高零件高温拉伸强度和高温持久性能。试验结果表明,在激光线输入量为300J/m时,成形体致密度最高,为98.9%,成形体沿层间方向组织为树枝晶加等轴晶,在层内方向组织为等轴晶。采用心部+后轮廓扫描的方式,轮廓激光线输入量为100J/m时表面质量最优,粗糙度为3.1μm。对成形体采用1 065℃固溶+双时效的热处理可以获得最佳高温性能组合,高温拉伸强度为1 356MPa,高温持久时间为34h。结果显示,通过激光选区熔化制作IN718镍基超合金可以满足航空结构件对致密度、表面质量和高温性能要求。     

SLM铺粉设备的误差分析及控制方法

自行设计、制造了一套铺粉装置。介绍了该铺粉装置的主要组成和工作原理;重点分析了铺粉装置的误差来源:如刮板刃口的直线度和运动误差、成型缸活塞运动误差、基板平面与推动丝杠轴线的垂直度等。提出了误差的计算方法,重点论述了刮板运动误差的放大效应,给出了计算公式。实践表明:可以通过采用专业高精度线性模组等措施控制、消除误差。     

Build orientation determination of multi-feature mechanical parts in selective laser melting via multi-objective decision making

Selective laser melting (SLM) is a unique additive manufacturing (AM) category that can be used to manufacture mechanical parts. It has been widely used in aerospace and automotive using metal or alloy powder. The build orientation is crucial in AM because it affects the as-built part, including its part accuracy, surface roughness, support structure, and build time and cost. A mechanical part is usually composed of multiple surface features. The surface features carry the production and design knowledge, which can be utilized in SLM fabrication. This study proposes a method to determine the build orientation of multi-feature mechanical parts (MFMPs) in SLM. First, the surface features of an MFMP are recognized and grouped for formulating the particular optimization objectives. Second, the estimation models of involved optimization objectives are established, and a set of alternative build orientations (ABOs) is further obtained by many-objective optimization. Lastly, a multi-objective decision making method integrated by the technique for order of preference by similarity to the ideal solution and cosine similarity measure is presented to select an optimal build orientation from those ABOs. The weights of the feature groups and considered objectives are achieved by a fuzzy analytical hierarchy process. Two case studies are reported to validate the proposed method with numerical results, and the effectiveness comparison is presented. Physical manufacturing is conducted to prove the performance of the proposed method. The measured average sampling surface roughness of the most crucial feature of the bracket in the original orientation and the orientations obtained by the weighted sum model and the proposed method are 15.82, 10.84, and 10.62 μm, respectively. The numerical and physical validation results demonstrate that the proposed method is desirable to determine the build orientations of MFMPs with competitive results in SLM.     

激光选区熔化自由制造异质材料零件技术研究

为解决当前激光选区熔化成型过程难以按需在零件任意位置自由布置不同材料的难题,基于多漏斗供粉+柔性清扫回收粉末原理,对异质材料零件激光选区熔化增材制造技术展开了研究,详细探讨了成型机理、粉尘污染防范机制及异质材料数据处理方法。采用CuSn10、4340两种不同的合金材料进了工艺实验验证。实验表明该方法可以较有效解决激光选区熔化成型过程异质材料布置难题,实现异质材料零件成型：（1）能自由地在不同层间或同层内不同区域按需布置不同的材料;（2）所得块状异质材料零件的铜合金材料区域Fe元素平均质量百分含量可控制在2%以下,钢材料区域Cu元素平均质量百分含量可控制在1%以下;（3）成功成型了一个具有复杂外形及微细材料区域特征的异质材料齿轮零件,零件异质材料区域不受零件复杂外形限制,可自由按需布置材料,0.5mm宽的层内异质材料区域也能被较好地表达出来,尺寸误差不超过±0.1mm。     

基于选区激光融化成型的空间曲线啮合轮后处理工艺及传动性能研究

采用选区激光熔化(SelectiveLaserMelting,SLM)快速成型设备与316L不锈钢粉末,得到的空间曲线啮合轮样品表面粗糙度值较大,主动轮与从动轮不能实现连续稳定的啮合传动。为了研究选区激光熔化成型的空间曲线啮合轮的表面后处理工艺,采用机械喷砂与电解抛光相结合的加工方法得到的主动轮与从动轮样品,表面粗糙度值达到Ra 1.0μm。实验结果表明,采用的后处理工艺和参数获得的主动轮与从动轮样品具有较高的形状精度与尺寸精度,能够实现连续稳定的啮合传动。此方法为空间曲线啮合轮提供了较好的制造思路。     

Metal-ceramic bond mechanism of the Co-Cr alloy denture with original rough surface produced by selective laser melting

The porcelain fracture caused by low metal-ceramic bond strength is a critical issue in porcelain fused to metal（PFM） restorations. Surface roughening methods, such as sand blasting, acid etching and alkaline degreasing for the metal matrix are used to increase bond strength. However, the metal matrix of PFM processed by selective laser melting（SLM） has natural rough surface. To explore the effect of the original roughness on metal-ceramic bond strength, two groups of specimen are fabricated by SLM. One group of specimen surface is polished smooth while another group remains the original rough surface. The dental porcelain is fused to the specimens＇ surfaces according to the ISO 9693：1999 standard. To gain the bond strength, a three-point bending test is carried out and X ray energy spectrum analysis（EDS）, scanning electron microscope（SEM） are used to show fracture mode. The results show that the mean bond strength is 116.5 16 MPa of the group with rough surface（Ra= 17.2）, and the fracture mode is cohesive. However, when the surface is smooth （Ra =3.8）, the mean bond strength is 74.5 MPa _＋ 5 MPa and the fracture mode is mixed. The original surface with prominent structures formed by the partly melted powder particles, not only increases surface roughness but also significantly improves the bond strength by forming strong mechanical lock effect. Statistical analysis （Student＇s t-test） demonstrates a significant difference （p〈0.05） of the mean value of bond strength between the two groups. The experiments indicate the natural rough surface can enhance the metal-ceramic bond strength to over four times the minimum value （25 MPa） of the ISO 9693：1999 standard. It is found that the natural rough surface of SLM-made PFM can eliminate the porcelain collapse defect produced by traditional casting method in PFM restorations.     

电子束选区熔化技术的粉末预热系统设计

通过对电子束选区熔化技术中金属粉末的预热方式进行分析和比较,得出了成形底板采用加热板和成形活塞缸上部采用环形加热器进行粉末预热的两种热传导方案;采用短波段的红外辐射灯,并通过旋转装置保证粉末预热和辐射灯不被金属蒸气蒸镀.金属粉末预热后的成形效果明显提高.     

金属构件选区激光熔化快速成型铺粉控制系统研究

选区激光熔化（SLM,Selective Laser Mching)技术是直接将选区内金属或合金粉末逐层熔化,堆积成一个冶金结合,组织致密的实体,其外形不需进一步加工,经抛光或简单表面处理可直接作模具。本文是在自行研制的国内首台金属构件直接选区激光熔化实验样机设备基础上,介绍分析了该设备的控制系统,重点介绍了选区激光熔化设备铺粉控制系统,它是该技术能否达到预期目标的关键因素之一,并且对其铺粉精度进行了试验验证,为金属构件直接选区激光熔化成型工艺研究奠定了基础。     

Dynamic confocal scanning laser microscopy methods for studying milk protein gelation and cheese melting

Dynamic confocal scanning laser microscopy (CSLM) methods were developed to enable observation of milk protein gelation and cheese melting. Protein aggregation and the formation of gel networks in renneted full-fat and low-fat milks and glucono-δ-lactone (GDL)-acidified skim milks were observed by CSLM and observations correlated with increases in shear modulus (G′) and dynamic viscosity (η*) as determined by dynamic amplitude oscillatory rheology. Confocal scanning laser microscopy observation of low-fat and full-fat cheeses showed changes in fat distribution and an increase in staining intensity during cheese melting.     

电子束选区熔化技术的控制系统设计

通过对电子束选区熔化技术控制系统的功能需求进行分析,得到了以PMAC数控卡作为控制系统下位机的控制方案,不仅可以对4个步进电机及限位信号进行运动控制,而且可以进行扫描数据的存储、下载、计算及运行.两年多的运行表明该控制方案具有较高的可靠度.     

激光选区烧结成型材料的研究和应用现状

介绍激光快速成型的原理及SLS对材料性能的要求,概括激光选取烧结成形技术中各种材料的研究和应用现状,分析SLS技术产业化存在的问题及可能解决的途径。     

Ni-Cr-B-Si激光熔覆层与H62黄铜基材间显微组织及微区分析

首次探讨了在H62黄铜基材料上激光熔覆镍基合金的可能性.并利用扫描电镜(SEM)对显微组织进行了观察,分析了熔覆层、结合区及热影响区的组织形貌及成分变化.研究结果表明,利用高能量密度的激光束熔覆涂层,使显微组织明显细化.覆层组织主要由r-Ni、Ni₃B、CrB、M₂₃(CB)₆组成.覆层与基体间形成了冶金结合.基体受温度梯度影响产生了组织粗化的热影响区.     

多零件选区激光熔化成型效率的优化

对多零件选区激光熔化的成型效率进行了优化.首先,分析了多零件选区激光熔化成型过程的时间消耗,并以减少时间消耗为目标建立了3维零件在3维成型空间中的2.5维排料优化规则.然后,研究了2.5维自动排料,提出利用3维零件模型在2维平面区域的投影将2.5维排料转化为2维排料的简化方法和一种利用切片数据进行投影生成的算法.最后,为验证所述方法的有效性,以手术模板模型为例,在虚拟选区激光熔化系统VDemetal280上进行了优化实验.与优化前相比,优化后的成型次数从4次降为3次,在扫描速度为600 mm/s、切片层厚为0.035 mm、扫描间距为0.08mm的工艺参数下,总铺粉次数从3 892次降为2 231次,预计加工时间从约91 276 s降为69 918 s,时间消耗有明显减少.     

选择性激光烧结激光能量密度与温度补偿规律研究

选择性激光烧结（SLS）成型预热温度从成型缸中间到缸壁呈降低趋势,由于预热温度不均匀,导致SLS成型件密度不均匀。针对这一问题,通过增加激光能量密度对预热温度不足进行了补偿。通过试验建立了激光能量密度差△E与预热温差△T的经验公式,并比较了温度补偿前后烧结件的机械强度。实验结果表明,通过增加激光能量密度对预热温度不足进行补偿,提高了产品机械强度。     

Scanning electron microscopy and transmission electron microscopy microstructural investigation of high-speed tool steel after Nd:YAG pulsed laser melting

This article presents the microstructure of a pulsed Nd:YAG laser‐melted high‐speed steel, namely HS6‐5‐2. The high chemical homogeneity and fine structure of the melted zone was attributed to high cooling rates due to the short duration of interaction with the Nd:YAG pulsed laser radiation and the relatively small volume of the melted material. The structure obtained in the surface layer after laser melting has a high level of hardness and shows improved wear resistance.     

In situ monitoring of selective laser melting using plume and spatter signatures by deep belief networks

Critical quality issues such as high porosity, cracks, and delamination are common in current selective laser melting (SLM) manufactured components. This study provides a flexible and integrated method for in situ process monitoring and melted state recognition during the SLM process, and it is useful for process optimization to decrease part quality issues. The part qualities are captured by images obtained from an off-axis setup with a near-infrared (NIR) camera. Plume and spatter signatures are closely related to the melted states and laser energy density, and they are employed for the SLM process monitoring in an adapted deep belief network (DBN) framework. The melted state recognition with the improved DBN and original NIR images requires little signal preprocessing, less parameter selection and feature extraction, obtaining the classification rate 83.40% for five melted states. Compared to the other methods of neural network (NN) and convolutional neural networks (CNN), the proposed DBN approach is identified to be accurate, convenient, and suitable for the SLM process monitoring and part quality recognition.     

Effect of Fe2O3 content on microstructure of Al powder consolidated parts via selective laser melting using various laser powers and speeds

In situ constituents were formed inside an aluminium matrix via selective laser melting (SLM) of Al powder mixed with 5, 10, and 15 wt% Fe₂O₃ powder (using various laser powers and speeds), in order to investigate the effect of Fe₂O₃ content on the microstructural characteristics of novel aluminium matrix composites. The unique microstructures such as coralline-like Al–Fe intermetallics were formed by the in situ reaction, being Fe₃Al at first but Al₁₃Fe₄ soon after that. These coralline-like intermetallics were fragmented (under appropriate laser parameters and/or higher Fe₂O₃ contents) and mixed up with Al oxide particles, reinforcing the matrix. The higher Fe₂O₃ increased the formation of other combinations such as Al₂Fe, AlFe, and Fe₃Al as well as metastable Al oxides in addition to equilibrium Al₁₃Fe₄ (Al₃Fe) and stable α-Al₂O₃. A very fine, well-bonded, and homogeneous distribution of hard particles was achieved in high Fe₂O₃ contents, efficiently increasing the hardness and providing an advanced Al matrix composite.