激光增材制造温度场检测分析与控制综述 
下载： 1636次
1 引言
激光金属增材制造(3D打印、激光金属成形)是20世纪末发展起来的新兴技术,根据计算机CAD模型数据,通过高功率激光使合金粉末或丝材快速原位冶金熔化、凝固和逐层堆积,实现复杂金属零件的直接近净成形。具有成形件晶粒细小均匀,制造周期短,无需锻铸工业装备及模具,材料利用率高,工艺柔性高,可以制备传统工艺难以实现的复杂形状零件等独特技术优势,在航空航天、核电、船舶等重大装备制造领域具有广阔的应用前景[1-3]。近年来,激光金属增材制造成为先进制造技术领域的研究热点,在世界范围内受到高度关注。
激光金属增材制造的工艺方法主要包括基于粉末床的激光选区熔化(SLM)、基于喷嘴跟随送粉的激光熔覆沉积(LCD)和熔丝增材制造等[4-7]。增材制造过程中的非平衡物理冶金和热物理过程十分复杂,同时伴随着激光、粉末、固体基材、熔池的交互作用,移动熔池的快速凝固收缩,温度梯度大,零件长时间经历高能激光束的周期性、剧烈和非稳态的循环加热、冷却及短时非平衡循环固态相变,在零件内产生热应力和应力集中,导致宏观翘曲变形和开裂,产生微裂纹、微气孔等冶金缺陷,造成零件显微组织性能降低[8-12]。因此,对增材制造温度场进行检测、分析与控制,降低温度梯度,以减少热应力、热变形和缺陷,提高成形精度,优化组织性能,一直是金属增材制造领域的关键问题之一。
本文总结了近年来国内外在增材制造温度场仿真分析、在线检测分析、温度在线控制等方面的研究进展,并对未来的发展趋势进行了分析与预测,这对充分认识增材制造温度场检测、分析与控制的研究重点、难点,找准突破方向具有积极的意义。
2 增材制造温度场仿真分析
2.1 仿真分析基本原理
激光金属增材制造的温度场分析属于典型的非线性瞬态热传导问题,满足三维瞬态热传导控制微分方程[13-14]。
式中:ρ为材料密度,c为材料比热容,T为瞬时温度值,t为激光与基体相互作用的时间,k为材料热传导率,Q为内热源的强度。
增材制造热场仿真分析实际上是设置边界条件,建立适当的激光热源模型,采用有限元分析软件对(1)式进行求解的过程。
2.2 研究现状
加拿大滑铁卢大学的Zhang等[15]在SLM成形17-4PH不锈钢的热传导有限元仿真模型中,以三维立体热源表达式代替传统的二维高斯热源表达式,并考虑了材料的各向异性增强导热系数和激光吸收率对热传导过程的影响,能够根据成形工艺参数精确预测熔池形态和尺寸、熔道稳定性和波纹角(
图 1. 仿真SLM熔道波纹角(下)和真实波纹角(上)的比较[15]
Fig. 1. Comparison of simulation of SLM ripple-angle θ of track (down) and real ripple-angle (up)[15]
图 2. 热力耦合仿真预测SLM悬臂梁的热应力和热变形[17]
Fig. 2. Prediction of thermal stresses and distortion of SLM cantilever by coupled thermo-mechanical simulation[17]
图 3. 45钢基板上LCD成形 Fe50铁基合金温度场仿真[21]
Fig. 3. Temperature field simulation of Fe50 alloy LCD on a 45 carbon steel base board[21]
图 4. 镍基合金LCD成形熔池三维温度及对流速度分布仿真[23]。(a)温度场;(b)热对流速度场
Fig. 4. 3D Simulation of temperature and convection velocity distribution of Ni-based alloy LCD melt pool [23]. (a) Temperature field; (b) heat convection velocity field
3 增材制造温度场在线检测
3.1 测温基本原理
增材制造温度场在线检测大都采用非接触式热辐射检测,其中基于红外热辐射的测温仪器有红外热像仪(区域测温)、双色高温计(点测温)、单色高温计(点测温,精度低于双色高温计);基于可见光波段热辐射的检测方法有CCD相机、高速相机(区域测温)。热辐射测温的主要依据是普朗克黑体辐射理论[27-28]。该理论中黑体光谱辐射出射度与波长、温度的关系为
式中:M(λ,T)为波长λ、温度T的黑体光谱辐射出射度;C1、C2分别为普朗克第一、第二辐射常数。
此外,也有少量关于应用热电偶进行接触式增材制造温度检测的研究。
3.2 无反馈控制的温度在线检测
英国伦敦帝国理工学院的Hooper[29]在SLM成形系统中集成了光路与扫描激光束同轴的两台Photron FASTCAM SA5高速相机,获取熔池发出的700 nm(可见光)和950 nm(红外)两个波长的辐射图像,实现了对Ti-6Al-4V钛合金SLM熔池温度的实时抗干扰检测(
图 5. 基于高速相机的SLM熔池温度检测[29]。(a)两台激光束光路同轴高速相机;(b)一条单道扫描中的熔池温度图像
Fig. 5. Detection of SLM melt pool temperature based on high-speed camera [29]. (a) Two high-speed cameras coaxial to the laser beam path; (b) melt pool temperature image of a single track
图 6. 基于红外热像仪的LCD温度场检测[32]。(a)红外热像仪及成形中的棒形试件;(b)试件及熔池温度分布图像
Fig. 6. Detection of LCD temperature field based oninfrared camera[32]. (a) Infrared camera and cylindrical specimens during deposition process; (b) temperature distribution image of sample and melt pool
图 7. 基于双色高温计的LCD熔池和熔道温度检测[33]。(a)温度检测原理图;(b)熔道固定点温度波动曲线;(c)熔池温度波动曲线
Fig. 7. Temperature detection of LCD melt pool and track based on two-color pyrometers[33]. (a) Schematic diagram of temperature detection; (b) temperature curve at the fixed location of the track; (c) temperature curves of the melt pool
3.3 温度在线检测与闭环控制
比利时的Devesse等[42]采用高光谱相机在线检测SLM激光熔池的温度,根据熔池温度实时调整激光功率,进行熔池温度线性状态反馈及比例积分(PI)控制以保持熔池温度及尺寸稳定。湖南大学的张荣华等[43]建立了基于状态空间方程的LCD熔池温度预测控制系统,利用双色高温计采集熔池温度,根据检测结果实时调节激光功率实现对熔池温度地预测控制,以保持其温度稳定,提高了单道多层试件的尺寸精度。苏州大学的孙华杰[44]采用双CCD相机对Fe313 铁基合金LCD成形熔池进行双通道测温以提高检测精度,并根据检测结果对激光功率进行闭环控制,提高了成形零件的尺寸精度、表面光洁度,减小了显微组织差异。合肥工业大学的沈初杰等[45]利用双色高温计检测LCD成形中的熔池温度,并与设定的熔池温度值进行比较,根据比较结果对激光功率进行反馈控制,提高了316L不锈钢薄壁圆环成形件的尺寸精度。美国密歇根大学的Song等[46]在LCD成形中根据双色高温计检测的熔池温度和CCD相机检测的熔覆层高度对激光功率实施闭环控制(
图 8. LCD熔池温度闭环反馈控制[46]。(a) LCD工艺闭环控制原理图;(b)采用与未采用闭环控制制作316L不锈钢涡轮叶片的比较
Fig. 8. Melt pool temperature feedback control in LCD process[46]. (a) Schematic diagram of LCD process with closed loop control; (b) 316L stainless steel turbine blades manufactured with and without control
4 增材制造温度场在线预热控制
捷克的Maly等[52]在SLM成形Ti-6Al-4V试件时,发现将基板在线预热至200~550 ℃,可以有效降低成形零件的温度梯度、减少热应力和热变形,预热温度与热变形的减少程度呈线性关系,但温度过高会导致未熔钛合金粉末的化学成分发生变化。日本的Sato等[53]以不同的基板预热温度SLM成形金属Ti时,通过同步辐射X射线监测钛粉末的熔化和凝固过程,发现随着预热温度升高,熔化钛微滴和基板的接触角减小,增加了基板的润湿性,减少了粉末溅射,从而使成形件的表面更光滑。英国谢菲尔德大学的Ali等[54]针对SLM成形Ti-6Al-4V试件时温度梯度大导致残余应力大,熔池迅速凝固形成马氏体组织导致材料延展性低的问题,对SLM成形基板进行高温预热以降低温度梯度。结果表明,当基板预热至570 ℃时可以使α'马氏体组织分解为平衡α+β组织,强度和延伸率分别提高3.2%和66.2%,显著降低了残余应力,提高了强度和延展性。比利时的Mertens等[55]比较了Al7075铝合金、哈氏镍合金、H13工具钢、CoCr合金四种材料SLM成形时,基板预热对成形件降低热应力、减少裂纹缺陷、改善显微组织性能的不同影响,基板预热至400 ℃与未预热LCD成形的Al7075试件的显微组织如
图 9. 基板未预热与预热LCD成形的Al7075试件显微组织[55]
Fig. 9. Microstructure ofAl7075 LCD samples built without and with preheating[55]
图 10. 通过基板预热减小SLM成形AlSi10Mg悬臂梁热变形的效果[60]。(a)未预热;(b)预热至200 ℃
Fig. 10. Effect of reducing thermal deform of AlSi10Mg SLM cantilevers by substrate preheating[60]. (a) On non-preheated substrate; (b) with a preheating temperature of 200 ℃
图 11. 基板未预热与预热熔覆的Stellite 1显微组织[63]。(a)未预热;(b)预热
Fig. 11. Microstructures of the deposited Stellite 1 on non-preheated and preheated substrates[63]. (a) On non-preheated substrate; (b) on preheated substrate
5 结论
通过对激光金属增材制造温度场检测、分析与控制的研究进展进行讨论,得出以下结论:
1) 目前金属增材制造温度场方面的研究,大部分基于有限元仿真分析,包括对SLM和LCD等工艺的激光熔池、高温熔道、激光扫描路径、成形表面、整个增材制造零件的温度场以及成形过程热力耦合的有限元仿真。通过温度场仿真,预测拟采用的材料、工艺参数、扫描路径对增材制造零件温度梯度大小及温度分布的影响,以及可能产生的热应力、热变形,从而选择温度梯度最小的工艺方案,减少制件废品率,因此有限元仿真在增材制造热场分析领域始终发挥着重要的作用。金属增材制造是一个多物理场耦合的过程,成形过程受到保护气流、粉末飞溅、成形缺陷等诸多不稳定因素的影响,但仿真过程中通常对这些不稳定因素进行简化处理,甚至忽略,所以仿真分析的结果与实际的增材制造温度场必然存在偏差。增材制造温度场有限元仿真研究主要是对仿真建模过程的改进,以不断减小仿真温度场与实际温度场的差异。例如,激光束对熔池形态、尺寸及温度分布具有明显的影响,传统的SLM增材制造温度场仿真采用二维高斯激光束热源模型,但激光束在SLM成形中可以透射进粉末床内部而不仅仅是照射在表面,因此可以采用三维激光束热源模型代替二维高斯激光束热源模型;增材制造的晶体成长方向使成形材料具有各向异性,因此可以采用各向异性的导热系数;针对增材制造粉末流、保护气流、熔池马拉戈尼对流效应等不稳定因素引起的瞬态温度场变化进行仿真,可以明晰各种不稳定因素对增材制造零件温度分布的影响规律。
2) 增材制造温度场在线检测包括点测温和区域测温两种方式。LCD工艺非接触式点测温主要是通过将双色高温计探头等固定在熔覆头旁侧,在成形过程中探头伴随熔覆头一起运动,瞄准熔池进行测温,获取点温度数据。红外热像仪、CCD相机等可以获取SLM、LCD熔池乃至整个成形表面的温度分布数据,但对熔池温度的检测精度低于双色高温计点测温。热电偶接触式测温精度较高,可用于增材制造中的固定点测温,或红外高温计等非接触式测温设备的初始温度标定。但缺点是需要焊接在零件内部,会破坏零件的完整性,且在成形中随着零件高度的不断增加,得到的温度信号也越弱。
在增材制造温度场闭环控制方面,主要根据在线检测的熔池温度与设定温度的偏差,对激光功率进行反馈控制,以提高成形精度,降低热应力及热变形,减少缺陷的产生。这方面的研究虽然较多,但实现温度场闭环控制的最新研究较少,原因是零件温度发生变化相对于激光功率的调整有明显的滞后,因此反馈控制对降低零件温度梯度虽有积极的作用,但实际效果未达到理想的水平。为了克服反馈控制的不足,最新的研究是根据在线检测的熔池温度,预测熔池下一个时间段的温度变化趋势,提前进行激光功率调节,即预测控制,以达到最好的熔池温度控制效果。但仅检测熔池温度并不能充分反映整个零件的温度分布,因此增材制造温度场闭环控制未来的研究方向应该是对整个成形表面的温度场进行在线检测分析,根据分析结果预测成形表面的温度变化趋势,对激光功率等参数进行提前控制,才能达到整个零件的温度梯度最小化的理想效果。
3) 对成形基板、成形表面进行在线预热也能在一定程度上降低增材制造零件温度梯度,减少热变形、热变形和缺陷,提高零件力学性能。SLM工艺由于已成形零件覆没在成形缸粉末材料中,便于加热,因此预热法在SLM成形中应用较为普遍,通常是通过基板预热使SLM已成形零件和粉末床加热至设定温度。在LCD增材制造中预热方法以基板加热法为主,也有少数采用成形表面照射/辐射加热法。预热法虽然能够降低增材制造零件的温度梯度,但过高的预热温度会导致粉末床、成形表面和基板上的金属粉末的化学成分发生变化,或引起偏析缺陷,故预热温度不能过高。基板预热的优点是简便易行,可整体性提高成形零件的温度,但不能根据成形表面的温度分布梯度对不同的区域给予不同的热量输入。在LCD工艺中,如采用基板加热法,在成形中随着零件高度的增加,通过基板预热传输至成形表面的热量将逐渐减少,有可能存在成形表面不能预热到设定温度的情况。
综上所述,预热法虽不能完全消除增材制造零件的温度梯度,但仍是降低温度梯度的有效辅助手段,如与增材制造温度场在线检测以及闭环控制相配合,先通过预热初步减小温度梯度,再通过温度场在线检测与闭环控制进一步降低零件成长方向和成形表面不同区域的温度梯度,将达到更好的增材制造温度场控制效果。
[1] 王华明. 高性能大型金属构件激光增材制造: 若干材料基础问题[J]. 航空学报, 2014, 35(10): 2690-2698.
[2] Lu B H, Li D C, Tian X Y. Development trends in additive manufacturing and 3D printing[J]. Engineering, 2015, 1(1): 85-89.
[3] Lewandowski J J, Seifi M. Metal additive manufacturing: a review of mechanical properties[J]. Annual Review of Materials Research, 2016, 46(1): 151-186.
[4] Ngo T D, Kashani A, Imbalzano G, et al. Additive manufacturing (3D printing): a review of materials, methods, applications and challenges[J]. Composites Part B: Engineering, 2018, 143: 172-196.
[5] Murr L E. A metallographic review of 3D printing/additive manufacturing of metal and alloy products and components[J]. Metallography, Microstructure, and Analysis, 2018, 7(2): 103-132.
[6] 杨永强, 陈杰, 宋长辉, 等. 金属零件激光选区熔化技术的现状及进展[J]. 激光与光电子学进展, 2018, 55(1): 011401.
[7] 李祚, 隋尚, 袁子豪, 等. 高沉积率激光熔覆沉积GH4169合金的微观组织与拉伸性能[J]. 中国激光, 2019, 46(1): 0102004.
[8] Cao L, Chen S Y, Wei M W, et al. Effect of laser energy density on defects behavior of direct laser depositing 24CrNiMo alloy steel[J]. Optics & Laser Technology, 2019, 111: 541-553.
[9] Liu QC, ElambasserilJ, Sun SJ, et al., 2014, 891/892: 1519- 1524.
[10] Gong H J, Rafi K, Gu H F, et al. Influence of defects on mechanical properties of Ti-6Al-4V components produced by selective laser melting and electron beam melting[J]. Materials & Design, 2015, 86: 545-554.
[11] Xie R D, Li D C, Cui B, et al. A defects detection method based on infrared scanning in laser metal deposition process[J]. Rapid Prototyping Journal, 2018, 24(6): 945-954.
[12] 孙洪吉, 韦靖, 郑兆宏, 等. 激光工艺参数对激光熔化沉积纯钛样品残余应力的影响[J]. 中国激光, 2019, 46(3): 0302014.
[13] Carslaw HS, Jaeger JC. Conduction of heat in solids[M]. 2nd ed. Oxford: Clarendon Press, 1986.
[14] 李雅莉. 选区激光熔化AlSi10Mg温度场及应力场数值模拟研究[D]. 南京: 南京航空航天大学, 2015.
Li YL. Numerical investigation on temperature field and stress field during selective laser melting of AlSi10Mg[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2015.
[15] Zhang Z D, Huang Y Z, Rani Kasinathan A, et al. 3-Dimensional heat transfer modeling for laser powder-bed fusion additive manufacturing with volumetric heat sources based on varied thermal conductivity and absorptivity[J]. Optics & Laser Technology, 2019, 109: 297-312.
[16] Arisoy Y M, Criales L E, Özel T. Modeling and simulation of thermal field and solidification in laser powder bed fusion of nickel alloy IN625[J]. Optics & Laser Technology, 2019, 109: 278-292.
[17] Schänzel M, Shakirov D, Ilin A, et al. Coupled thermo-mechanical process simulation method for selective laser melting considering phase transformation steels[J]. Computers & Mathematics With Applications, 2019, 78(7): 2230-2246.
[18] Panda B K, Sahoo S. Thermo-mechanical modeling and validation of stress field during laser powder bed fusion of AlSi10Mg built part[J]. Results in Physics, 2019, 12: 1372-1381.
[19] Du Y, You X Y, Qiao F B, et al. A model for predicting the temperature field during selective laser melting[J]. Results in Physics, 2019, 12: 52-60.
[20] Yin J, Peng G Y, Chen C P, et al. Thermal behavior and grain growth orientation during selective laser melting of Ti-6Al-4V alloy[J]. Journal of Materials Processing Technology, 2018, 260: 57-65.
[21] 王亚晨. 激光熔覆温度场模拟及激光扫描顺序方法研究[D]. 乌鲁木齐: 新疆大学, 2018
Wang YC. Simulation of temperature field in laser cladding and study of laser scanning sequence method[D]. Urumqi: Xinjiang University, 2018.
[22] Zhang D Y, Feng Z, Wang C J, et al. Modeling of temperature field evolution during multilayered direct laser metal deposition[J]. Journal of Thermal Spray Technology, 2017, 26(5): 831-845.
[23] Gan Z T, Liu H, Li S X, et al. Modeling of thermal behavior and mass transport in multi-layer laser additive manufacturing of Ni-based alloy on cast iron[J]. International Journal of Heat and Mass Transfer, 2017, 111: 709-722.
[24] Gan Z T, Yu G, He X L, et al. Numerical simulation of thermal behavior and multicomponent mass transfer in direct laser deposition of co-base alloy on steel[J]. International Journal of Heat and Mass Transfer, 2017, 104: 28-38.
[25] Duan W, Yin Y J, Zhou J X. Temperature field simulations during selective laser melting process based on fully threaded tree[J]. China Foundry, 2017, 14(5): 405-411.
[26] Wei P, Wei Z Y, Chen Z, et al. Thermal behavior in single track during selective laser melting of AlSi10Mg powder[J]. Applied Physics A, 2017, 123(9): 604.
[27] 雷剑波. 基于CCD的激光再制造熔池温度场检测研究[D]. 天津: 天津工业大学, 2007.
Lei JB. Detection of laser remanufacturing molten pool temperature field based on CCD[D]. Tianjin: Tianjin Polytechnic University, 2007.
[28] Hudson RD. Infrared system engineering[M]. New York: John Wiley & Sons, Inc., 1969.
[29] Hooper P A. Melt pool temperature and cooling rates in laser powder bed fusion[J]. Additive Manufacturing, 2018, 22: 548-559.
[30] Lane B, Whitenton E, Moylan S. Multiple sensor detection of process phenomena in laser powder bed fusion[J]. Proceedings of SPIE, 2016, 9861: 986104.
[31] Lane B, Moylan S, Whitenton E P, et al. Thermographic measurements of the commercial laser powder bed fusion process at NIST[J]. Rapid Prototyping Journal, 2016, 22(5): 778-787.
[32] Marshall G J, Young W J, Thompson S M, et al. Understanding the microstructure formation of Ti-6Al-4V during direct laser deposition via in-situ thermal monitoring[J]. JOM, 2016, 68(3): 778-790.
[33] Li S M, Xiao H, Liu K Y, et al. Melt-pool motion, temperature variation and dendritic morphology of Inconel 718 during pulsed- and continuous-wave laser additive manufacturing: a comparative study[J]. Materials & Design, 2017, 119: 351-360.
[34] de Baere D, Devesse W, de Pauw B, et al. Spectroscopic monitoring and melt pool temperature estimation during the laser metal deposition process[J]. Journal of Laser Applications, 2016, 28(2): 022303.
[35] 袁钰函. 基于彩色CCD的激光熔池的温度场检测与研究[D]. 合肥: 合肥工业大学, 2018.
Yuan YH. Detection of laser molten pool temperature field based on CCD[D]. Hefei: Hefei University of Technology, 2018.
[36] 钦兰云, 徐丽丽, 杨光, 等. 钛合金激光沉积制造热累积与熔池形貌演化[J]. 稀有金属材料与工程, 2017, 46(9): 2645-2650.
Qin L Y, Xu L L, Yang G, et al. Correlations of thermal accumulation and melt pool geometry during laser deposition manufacturing of titanium alloy[J]. Rare Metal Materials and Engineering, 2017, 46(9): 2645-2650.
[38] 朱进前, 凌泽民, 杜发瑞, 等. 激光熔丝增材制造温度场的红外热像监测[J]. 红外与激光工程, 2018, 47(6): 0604002.
[39] 徐红祥. 选择性激光熔融成型层温度特性的研究[D]. 合肥: 合肥工业大学, 2018.
Xu HX. Study on temperature characteristics of selective laser melting forming layer[D]. Hefei: Hefei University of Technology, 2018.
[40] Segerstark A, Andersson J, Svensson L E. Evaluation of a temperature measurement method developed for laser metal deposition[J]. Science and Technology of Welding and Joining, 2016, 22(1): 1-6.
[41] Petrat T, Winterkorn R, Graf B, et al. Build-up strategies for temperature control using laser metal deposition for additive manufacturing[J]. Welding in the World, 2018, 62(5): 1073-1081.
[42] Devesse W, de Baere D, Hinderdael M, et al. Hardware-in-the-loop control of additive manufacturing processes using temperature feedback[J]. Journal of Laser Applications, 2016, 28(2): 022302.
[43] 张荣华, 宋立军. 激光增材制造熔池温度实时监测与控制[J]. 应用激光, 2018, 38(1): 13-18.
[44] 孙华杰. 基于彩色CCD的激光熔覆熔池温度闭环控制研究[D]. 苏州: 苏州大学, 2018.
Sun HJ. Research on close-loop control of molten pool temperature during laser cladding process based on color CCD[D]. Suzhou: Soochow University, 2018.
[45] 沈初杰, 赵宗仁, 袁自钧, 等. 基于温度控制的激光熔覆成形工艺研究[J]. 合肥工业大学学报(自然科学版), 2017, 40(5): 660-664.
Shen C J, Zhao Z R, Yuan Z J, et al. Research on laser cladding forming technology based on temperature control[J]. Journal of Hefei University of Technology(Natural Science), 2017, 40(5): 660-664.
[46] Song L, Bagavath-Singh V, Dutta B, et al. Control of melt pool temperature and deposition height during direct metal deposition process[J]. The International Journal of Advanced Manufacturing Technology, 2012, 58: 247-256.
[47] Miyagi M, Tsukamoto T, Kawanaka H. Adaptive shape control of laser-deposited metal structures by adjusting weld pool size[J]. Journal of Laser Applications, 2014, 26(3): 032003.
[48] Craeghs T, Bechmann F, Berumen S, et al. Feedback control of layerwise laser melting using optical sensors[J]. Physics Procedia, 2010, 5: 505-514.
[50] Tang L, Landers R G. Layer-to-layer height control for laser metal deposition process[J]. Journal of Manufacturing Science and Engineering, 2011, 133(2): 021009.
[51] Tang L, Landers R G. Melt pool temperature control for laser metal deposition processes: part I: online temperature control[J]. Journal of Manufacturing Science and Engineering, 2010, 132(1): 011010.
[52] Maly M, Höller C, Skalon M, et al. Effect of process parameters and high-temperature preheating on residual stress and relative density of Ti6Al4V processed by selective laser melting[J]. Materials, 2019, 12(6): 930.
[53] Sato Y, Tsukamoto M, Shobu T, et al. Preheat effect on titanium plate fabricated by sputter-free selective laser melting in vacuum[J]. Applied Physics A, 2018, 124(4): 288.
[54] Ali H, Ma L, Ghadbeigi H, et al. In-situ residual stress reduction, martensitic decomposition and mechanical properties enhancement through high temperature powder bed pre-heating of selective laser melted Ti6Al4V[J]. Materials Science and Engineering: A, 2017, 695: 211-220.
[55] Mertens R, Dadbakhsh S, Van Humbeeck J, et al. Application of base plate preheating during selective laser melting[J]. Procedia CIRP, 2018, 74: 5-11.
[56] 卞宏友, 翟泉星, 曲伸, 等. 基体预热下激光沉积修复GH4169合金温度场和应力场演变[J]. 应用激光, 2017, 37(3): 327-332.
[57] Ding C G, Cui X, Jiao J Q, et al. Effects of substrate preheating temperatures on the microstructure, properties, and residual stress of 12CrNi2 prepared by laser cladding deposition technique[J]. Materials, 2018, 11(12): 2401.
[58] Fang J X, Li S B, Dong S Y, et al. Effects of phase transition temperature and preheating on residual stress in multi-pass & multi-layer laser metal deposition[J]. Journal of Alloys and Compounds, 2019, 792: 928-937.
[59] Xu J J, Lin X, Guo P F, et al. The effect of preheating on microstructure and mechanical properties of laser solid forming IN-738LC alloy[J]. Materials Science and Engineering: A, 2017, 691: 71-80.
[60] Buchbinder D, Meiners W, Pirch N, et al. Investigation on reducing distortion by preheating during manufacture of aluminum components using selective laser melting[J]. Journal of Laser Applications, 2014, 26(1): 012004.
[61] Zhang K, Wang S J, Liu W J, et al. Effects of substrate preheating on the thin-wall part built by laser metal deposition shaping[J]. Applied Surface Science, 2014, 317: 839-855.
[62] Kempen K, Vrancken B, Buls S, et al. Selective laser melting of crack-free high density M2 high speed steel parts by baseplate preheating[J]. Journal of Manufacturing Science and Engineering, 2014, 136(6): 061026.
[63] Fallah V, Alimardani M, Corbin S F, et al. Impact of localized surface preheating on the microstructure and crack formation in laser direct deposition of Stellite 1 on AISI 4340 steel[J]. Applied Surface Science, 2010, 257(5): 1716-1723.
Article Outline
解瑞东, 朱尽伟, 张航, 崔滨, 张连重, 李涤尘, 高峰. 激光增材制造温度场检测分析与控制综述[J]. 激光与光电子学进展, 2020, 57(5): 050003. Ruidong Xie, Jinwei Zhu, Hang Zhang, Bin Cui, Lianzhong Zhang, Dichen Li, Feng Gao. Review of Detection, Analysis and Control of Temperature Field in Laser Additive Manufacturing[J]. Laser & Optoelectronics Progress, 2020, 57(5): 050003.
PDF全文
