Study of laminated object manufacturing with separately applied heating and pressing

To improve the hot-pressing process currently employed in laminated object manufacturing (LOM), an innovative heating-and-pressing separation system is proposed, and heat transfer problems of this system are investigated. A thermal model is first established. It is solved numerically by the finite element method (FEM) software ANSYS, and verified by experiments. Based on the numerical solution under various operating conditions, it is found that the operating temperature of an adhesive can be reached quickly when the heater is maintained at a higher temperature, corresponding to a deeper heat-affected zone. This shortcoming can be effectively reduced if the speed of the heater is increased. Hence, a higher heater temperature together with a higher moving speed is suggested to shorten processing time and promote manufacturing efficiency. Through analysis, the appropriate distance between the roller and the heater, so as to obtain finished parts of high quality, is determined.     

FDM工艺参数对成型精度影响的试验探究

在分析了打印速度、分层厚度、填充密度等工艺参数基础上,通过等体积率公式,得到不同打印速度下,打印截面分层厚度和挤出丝宽之间的理论关系,然后根据丝宽搭接模型,对水平方向的成型精度进行理论分析。设计试验通过配置30、40及50 mm/s的打印速度,0.1、0.2及0.3 mm的分层厚度值和90%的填充密度3个工艺参数,对理论分析进行试验验证。试验结果表明,分层厚度为0.2 mm,打印速度区间在30~40 mm/s,填充密度为90%时的参数组合,在保证成型件竖直方向精度的基础上得到了最优的水平方向精度。     

改善LOM型快速成形中胶厚均匀性的研究

ＬＯＭ制件中胶厚分布不均匀严重影响ＬＯＭ技术的成形精度和应用效益。文章实测了ＺＩＰＰＹ快速成形系统使用的粘胶的流变学性能,建立了粘胶热压应变的力学模型,对模型进行求解和修正,并据此提出改善粘胶分布均匀性的措施,其中采用热压辊与工作台联动技术可以显著减小胶厚分布的不均匀性。     

金属颗粒冷态高速微喷射增材制造工艺研究

针对金属零件三维自由直接成形工艺中普遍存在的高能耗、高热残余应力等问题,提出了金属颗粒冷态高速微喷射增材制造新工艺。以常温下的高压氮气作为加速气流,利用微喷枪将微米级的金属粒子加速至其临界速度以上形成沉积。针对高速微喷射增材制造平台搭建、具有高加速性能与高分辨率的微喷枪设计展开了研究,并在此基础上,进行了单点成形与单线成形的试验研究,通过最小特征尺寸的大小与稳定度分析新工艺成形精度与成形质量,通过微观结构与显微硬度分析新工艺成形件的基本力学性能。试验结果表明:在一定范围内,通过喷射压力的变化可以实现单点成形尺寸的线性可控,通过喷射压力与导轨移动速度可以实现直线成形线宽与层厚的线性可控;试验中的0.9 mm的最窄线宽与低于8%的线宽波动量保证了该工艺一定的加工精度与成形质量;致密的微观组织结构与较高的显微硬度值保证了该工艺成形件良好的力学性能;多层扫描时层与层之间致密结合保证了该工艺逐层累加制造的能力。研究表明,金属颗粒冷态高速微喷射是一种稳定可控,可行的增材制造新工艺。     

Simulation of surface generated during abrasive flow finishing of Al/SiCp-MMC using neural networks

Abrasive flow machining (AFM) is a multivariable finishing process which finds its use in difficult to finish surfaces on difficult to finish materials. Near accurate prediction of generated surface by this process could be very useful for the practicing engineers. Conventionally, regression models are used for such prediction. This paper presents the use of artificial neural networks (ANN) for modeling and simulation of response characteristics during AFM process in finishing of Al/SiC_p metal matrix composites (MMCs) components. A generalized back-propagation neural network with five inputs, four outputs, and one hidden layer is designed. Based upon the experimental data of the effects of AFM process parameters, e.g., abrasive mesh size, number of finishing cycles, extrusion pressure, percentage of abrasive concentration, and media viscosity grade, on performance characteristics, e.g., arithmetic mean value of surface roughness (R _a, micrometers), maximum peak–valley surface roughness height (R _t, micrometers), improvement in R _a (i.e., ΔR _a), and improvement in R _t (i.e., ΔR _t), the networks are trained for finishing of Al/SiC_p-MMC cylindrical components. ANN models are compared with multivariable regression analysis models, and their prediction accuracy is experimentally validated.     

开关磁阻电动机实验平台的开发与研究

为研究开关磁阻电动机的运行特性与调速性能,在分析开关磁阻电动机的基本原理与控制方式的基础上,设计了基于数字信号处理器TMS320F2812的四相8/6极开关磁阻电动机实验平台,详细介绍了该平台硬件电路的原理、特性和软件程序的功能、流程;最后,基于所开发的实验平台对开关磁阻电动机进行了多项实验研究。研究结果表明,所开发的实验平台的软、硬件设计具有正确性和有效性,同时也证明了在速度PID控制下,开关磁阻电动机具备优异的调速性能。     

Experimental investigation of spherical bearings lubricated with non-newtonian fluids

In this paper are presented the results of an experimental programme designed to investigate the performance characteristics of externally pressurized spherical bearings lubricated with non-newtonian fluids taking into consideration the effect of film thickness, rotational speed and concentration of polymer in tap water.The results of the experimental work are presented and compared with the theoretical results given by Salem et al.     

Modeling of burr thickness in milling of ductile materials

Accuracy and surface finish play an important role in modern industry. The presence of undesired projections of materials, known as burrs, negatively affect the part quality and assembly process. To remove burrs, a secondary operation known as deburring is required for the post-processing and edge finishing of machined parts. The thickness of the burr is of interest as it describes the time and method necessary for deburring of the machined part. Burr thickness (B _t) measurements are costly and non-value-added operations that in most cases require the use of a scanning electron microscope for accurate burr characterization. Therefore, to avoid such expenses, the implementation of alternative methods for predicting the burr thickness is strongly recommended. In this research work, an analytical model for predicting the burr thickness in end milling of ductile materials is presented. The model is built on the geometry of burr formation and the principle of continuity of work at the transition from chip formation to burr formation that also takes into account the cutting force influence on burr formation. A very good correlation was found between the modeled and experimental B _t values. The model has shown a great sensitivity to material properties such as yield strength and specific cutting force coefficient (K _c). In addition, the sensitivity of the proposed model to the feed per tooth (f _t) and depth of cut (a _p) was considerably high. The proposed model allows the prediction of the thickness of the exit up milling side burr, without the need for experimental measurement and/or approximation of shear angle (Φ), friction angle (λ), and the tool chip contact length (L), unlike existing analytical burr size prediction models. Besides analytical modeling, statistical analysis is performed on experimental results in order to distinguish dominant process parameters on B _t. It is observed that the depth of cut and feed per tooth are the main parameters which significantly affect the B _t, while the speed has only a negligible effect on it.     

Software development for prediction of the weld bead in CMT and pulsed-MAG processes

Prediction of weld bead shapes prior to welding has been a challenge for researchers in recent years. The assurance of a weld shape with adequate penetration and dilution, good wetting angles and no undercuts leads to less repairing and reworking and thus, lower cost and time consumed. CMT is a variant of MIG/MAG welding process recently introduced in the market. Software control for bead-shape prediction helps the user to get familiar with this modern technology. In the present paper, two approaches were undertaken for software development. These were applied to CMT and pulsed-MAG welding and the results were compared. The graphical interface was built to help the user choose the welding parameters and get the representation of the weld bead profile. The two approaches used to predict the weld bead profiles are neural networks and interpolation method. The data entries for the two different methods are: welding process (CMT and MAG-pulsed), plate thickness, travel speed and wire feed speed. The output data is the complete welding profile defined by X and Y coordinates of the points on the welding profile. The neural networks were trained with different numbers of neurons, multiple layers and different networks, and welding data bases with different structures were used, in order to find the best fitting neural network. The final results for each method were checked against real profiles and it was concluded that the neural network method was more flexible and the accuracy of each methods was nearly the same.     

高速硬切削加工表面白层形成机理研究

白层是高速硬切削的特有现象,对加工表面完整性和零件的服役性能有着重要影响。针对高速硬切削加工表面白层问题,进行了对GCrl5淬硬轴承钢高速硬切削试验和表面白层测试,研究了不同切削条件下的白层形成机理,分析了切削速度和刀具磨损状态对白层特征的影响规律。分析结果表明,白层厚度随切削速度和后刀面磨损的增大而增大,而其分布的均匀性和连续性也将变差;切削速度和后刀面磨损的增加引起切削温度升高,导致加工表面快速淬火效应,使得白层厚度增大,其中切削速度的影响较为显著;在切削速度较低(100 m/min左右)时白层的形成机理主要为塑性变形,切削速度超过300 m/min则主要是马氏体相变所致,而在中间切削速度(200 m/min左右)时为2种机理的混合作用结果。     

Optimization of flux-cored arc welding process parameters by using genetic algorithm

The effect of flux-cored arc welding (FCAW) process parameters on the quality of the super duplex stainless steel (SDSS) claddings can be studied using Taguchi L9 design of experiments. In this experimental investigation, deposits were made with 30 % bead overlap. Establishing the optimum combination of process parameters is required to ensure better bead geometry and desired properties. The above objectives can be achieved by identifying the significant input process parameters as input to the mathematical models like welding voltage (X ₁), wire feed rate (X ₂), welding speed (X ₃), and nozzle-to-plate distance (X ₄). The identified responses governing the bead geometry are bead width (W) and height of the reinforcement (H). The mathematical models were constructed using the data collected from the experiments based on Taguchi L9 orthogonal array. Then, the responses were optimized using non-traditional nature-inspired technique like genetic algorithm (GA).     

Prediction modeling of Coriolis type mass flow: Sensor using neural network

The neural network (NN) technique has been utilized for prediction of performance of omegatube type Coriolis mass flow sensor. The results show that a well trained and well tested NN model has the capability to predict the performance of mass flow sensor for varying design parameters depending on the availability of the data and can be used as an alternative to the physical models in the sense that the results can be produced in a fast and cost effective way. The values of correlation coefficient (R) for the training, testing and whole datasets indicates that the NN results are in good agreement with the experimental results.     

CO_2热泵热水器的系统设计及试验研究

设计搭建了蒸发器和气冷器均采用套管式换热器的跨临界CO2热泵热水器性能测试试验台,在制冷剂充注量1.23kg时,通过调节膨胀阀的开度和控制气冷器的水流量来研究系统性能。结果表明:该机组能在较高COP(3.2)下制得65℃的热水,并可以在COP不低于2.0情况下制取80℃的热水;气冷器水流量对系统的COP、出水温度以及系统的排气压力影响最大;高效的换热器可以在压缩机排气温度一样的情况下提高出水温度,使系统在制取高温水时有更高的COP。     

分层实体制造快速成形工艺参数的人工神经网络预测

针对分层实体制造快速成形中工艺准备繁杂及工艺参数非线性的特点,提出分层实体制造快速成形工艺参数预测的人工神经网络方法,建立相应的人工神经网络模型,检验该模型用于分层实体制造工艺参数预测的合理性和可行性。     

基于并行核径向基神经网络的软测量与控制模型

转炉提钒过程中存在大量多元非线性因素,难以从统计学和机理上建立各操作参数与生产目标的优化控制模型,为优化转炉的操作参数,建立了基于径向基神经网络的半钢钒含量软测量和控制模型.径向基神经网络常用于非线性回归预测和控制,但是高维的核函数矩阵运算需要花费巨大计算资源.为了缩短计算时间,本文设计了并行算法用于计算径向基网络核函数矩阵,并将它用于转炉提钒软测量和控制模型,在以MPI构建的工作站机群上执行该算法,利用实际数据验证了该算法的加速性和准确性.     

磨削表面白层厚度影响因素的实验研究

通过淬硬轴承钢GCrl5的磨削实验,研究了砂轮速度、工件速度、磨削深度以及冷却方式等磨削参数对白层厚度的影响规律.实验表明:白层是由磨削过程中工件快速升温和快速冷却以及强烈的塑性变形引起的,白层厚度的变化是磨削加工过程中各种参数共同作用的结果,而其中磨削深度是主要原因,其次是砂轮速度和工件速度;白层厚度随砂轮速度和磨削深度的增大而增大;低的砂轮速度和磨削深度以及良好的冷却条件能有效抑制白层的产生.根据实验统计结果提出了预测磨削白层厚度的经验公式.     

Metal flow characteristics of local loading forming process for rib-web component with unequal-thickness billet

To explore the metal flow and filling law of large-scale rib-web component local loading forming process is important for fast design of unequal-thickness billet (UTB), parameter optimization and process control of the rib-web component local loading forming process. T-shaped component forming under UTB can reflect the forming characteristics in the large-scale rib-web component forming process. In the forming process by using UTB, the width of local loading changes dynamically, the thickness difference of billet changes notably, and the boundary conditions are very complex. By introducing new assumptions, variables and boundary conditions, a mathematical model for local loading pattern caused by UTB is established by using slab method (SM). Based on the virtualizing experimental data observed by finite element method (FEM), a predicted model for the dynamic width of local loading is established by using polynomial regression and partial least squares (PLS) regression. Comparing with FEM results indicates that the relative differences are less than about 10 % for predicted model of local loading width. Comparing with FEM and physical modeling experimental results indicates that the relative differences are less than about 15 % for SM model. The metal flow, cavity fill, and increased width of local loading under local loading condition are studied by using the mathematical models and numerical simulation, and the results indicate that: the metal flow and deformation pattern under local loading are determined by the thickness of billet and the width of local loading; the increased width of local loading is determined by initial geometric parameters, and the forming parameters such as materials (Ti-6Al-4 V and Ti-6Al-2Zr-1Mo-1 V), loading speed (0.1–1.0 mm/s), temperature (950–970 °C), etc. have little influence on it; the value of x _k (position of neutral layer) under local loading pattern caused by geometric parameters of billet is less than that caused by geometric parameters of die at initial forming stage.     

基于铣削力精确建模的工件表面让刀误差预测分析

航空航天制造业结构件的高速铣削加工中,在切削力作用下由整体铣削刀具挠度变形所引起的工件表面让刀误差,严重制约零件的加工精度和效率。针对这一问题,通过建立铣削力精确预测模型,结合刀具刚度特点,对工件让刀误差进行预测分析。将切削速度和刀具前角对切削力的影响规律引入二维直角单位切削力预测模型,并通过试验进行相关系数标定。借助等效前角将直角切削力预测系数应用到斜角切削力的预测,通过矢量叠加构建整体刀具三维切削力模型。分析刀具挠度变形对铣削层厚度及铣削接触中心角范围影响规律。基于离散化的刀具模型和切削力模型,建立铣削载荷条件下刀具等效直径悬臂梁模型弯曲变形计算方法。构建以刀具变形对铣削过程影响作用规律为反馈的刚性工件表面让刀误差及切削力柔性预测模型,通过整体铣刀铣削试验验证所建立理论模型的预测精度。     

基于PLC／WINCC／OPC的多电机系统平台的设计

针对多电机变频调速系统智能化控制的需要,设计出了基于西门子S7—300系列PLC的系统实验平台,该实验平台重点研究了系统的转速和张力的检测以及相关通讯（PROFIBUS、MPI、OPC）的设计,并以支持向量机广叉逆（SVMGI）解耦控制为例,通过对下位机程序的编写,验证了复杂智能控制在该实验平台应用的可行性。实验结果表明,该实验设计平台不但具有很高的稳定性和可靠性,而且还具有对多个量的检测功能,从而体现出了优越的控制性能。     

动态优化刮刀速度的新型涂层工艺

为提高活塞式无扰动涂层工艺的涂层质量,针对高分辨率激光快速成形系统涂层工艺中存在的涂层厚度随制件高度增加而变厚的问题,提出在制作过程中动态优化刮刀速度的涂层方法。研究刮刀速度、制件高度对涂层厚度的影响。采用面响应法,建立涂层厚度误差关于制件高度及刮刀速度的数学模型。根据该模型,在制作过程中随制件高度的变化,动态优化刮刀速度,实现涂层厚度均匀化。验证试验结果表明：与普通涂层工艺相比,新型涂层工艺将涂层厚度偏差由27 μm降为6.9 μm,解决了涂层厚度随制件高度增加而变厚的问题,实现涂层厚度的均匀化,提高堆积方向的制作精度。该涂层工艺也可应用于普通光固化激光快速成形系统中,解决制作陷阱结构时涂层厚度随制件高度变厚问题,因此该工艺对于光固化快速成形技术中提高堆积方向制作精度具有重要意义。