数据驱动的冷却水塔建模与节能优化操作

针对冷却水塔的节能操作给出了一种数据驱动的建模与优化方法。首先,基于冷却水塔实际运行数据,应用非负绞杀变量选择方法给出一个自适应模型用于描述冷却水塔过程,该模型对于冷却水塔出口水温具有良好的预测精度。根据变量选择结果,分析了外界空气温度与湿度对冷却能力的影响。然后,提出了基于模型的冷却水塔风机的优化操作策略,并进行实验将之应用于冷却水塔的操作。研究结果显示,基于模型的优化操作具有较大的节能空间。     

Surface performance of workpieces processed by electrical discharge machining in gas

The surface performance of workpieces processed by electrical discharge machining in gas(dry EDM)was studied in this paper.Firstly,the composition,micro hardness and recast layer of electrical discharge machined(EDMed)surface of 45 carbon steels in air were investigated through different test analysis methods.The results show that the workpiece surface EDMed in air contains a certain quantity of oxide,and oxidation occurs on the workpiece surface.Compared with the surface of workpieces processed in kerosene,fewer cracks exist on the dry EDMed workpiece surface,and the surface recast layer is thinner than that obtained by conventional EDM.The micro hardness of workpieces machined by dry EDM method is lower than that machined in kerosene,and higher than that of the matrix.In addition,experiments were conducted on the surface wear resistance of workpieces processed in air and kerosene using copper electrode and titanium alloy electrode.The results indicate that the surface wear resistance of workpieces processed in air can be improved,and it is related with tool material and dielectric.     

Structural Reliability Analysis for Implicit Performance with Legendre Orthogonal Neural Network Method

In order to evaluate the failure probability of a complicated structure, the structural responses usually need to be estimated by some numerical analysis methods such as finite element method (FEM). The response surface method (RSM) can be used to reduce the computational effort required for reliability analysis when the performance functions are implicit. However, the conventional RSM is time-consuming or cumbersome if the number of random variables is large. This paper proposes a Legendre orthogonal neural network (LONN)-based RSM to estimate the structural reliability. In this method, the relationship between the random variables and structural responses is established by a LONN model. Then the LONN model is connected to a reliability analysis method, i.e. first-order reliability methods (FORM) to calculate the failure probability of the structure. Numerical examples show that the proposed approach is applicable to structural reliability analysis, as well as the structure with implicit performance functions.     

微小型涡喷发动机向心涡轮的流动仿真

为了详细研究微型向心涡轮的内部流动特性,对一台自研微型涡轮发动机的涡轮进行了气动设计和全三维粘性数值模拟仿真,验证了叶片型线设计方案的可行性,得到模拟计算结果（落压比为1.91,总压绝热效率0.73,出口气流马赫数为1.2,流量13.8g/s）。研究了微型涡轮设计工况下内部的气流状态,对微尺寸下涡轮内部的流动特性及各种流动损失产生的特点及原因进行分析总结。结果表明：导向叶流道内的流动损失主要为由气体粘性引起的叶型损失;动叶流道中流动损失主要为气体在动叶前缘产生冲击形成的滞止损失与边界层损失,动叶出口叶片尾缘处形成的尾迹涡流损失。     

基于BP神经网络的铂铑热电偶的非线性校正

热电偶是工业中广泛使用的测温元件,由于其自身的物理特性的限制,其输出热电势与被测温度之间存在着一定的非线性,这将增大温度的测量误差,从而影响测量精度。针对这一问题,提出了基于BP神经网络的非线性校正算法,以热电偶的热电动势为输入信号,以与其相对应的温度值作为输出信号,给出了前馈型BP神经网络的结构和训练权值的方法。通过实验仿真结果对比可知,此方法降低了热电偶测温的非线性误差,便于操作,大大提高了铂铑热电偶在温度测量中的测量精度。     

齿轮参数激光测量系统运动学分析与仿真

齿轮参数激光测量系统的运动平稳性和可靠性是保证测量精度的重要因素。为了了解该测量机构的运动特性,通过使用Solidworks软件对齿轮参数激光测量系统进行实体建模,采用D-H法对该测量系统各个运动关节建立了坐标系并进行了正运动学分析。利用MATLAB中Robotics Toolbox工具箱,对该测量机构建立了运动学模型并对其进行了运动学仿真,对运动关节进行了轨迹规划仿真。通过运动仿真结果,可以更加清楚地了解测量系统在测量过程中的运动过程,对轨迹规划的仿真验证了运动机构的可靠性和平稳性。     

基于快速工艺决策的数字化制造管理平台研究与开发

针对制造业的数字化车间的各种工艺资源,建立了基于快速工艺决策的数字化制造管理平台,网络架构为三层客户机/服务器（C/S）结构,针对该平台,设计了具有应用层、功能层、接口层及数据库层的总体体系结构模型及多级权限管理结构模型,对车间各种工艺资源如机床、刀具、夹具、量具及切削用量等信息进行了有效的管理与维护,并可以与快速工艺决策系统之间进行数据交换,为快速工艺决策系统提供实时更新的工艺数据,进一步完善了企业车间的信息化与自动化建设。     

炭基/锌掺杂铁磁体复合材料制备及其消光性能研究

为了实现抗红外烟幕高效环保的要求,同时实现质轻、宽波段吸波性能,采用一步水热法制备了炭基-锰锌铁氧体/镍锌铁氧体/钴锌铁氧体复合材料的前驱体,并在500~900 ℃的温度区间进行焙烧得到了炭基/锌掺杂铁磁体复合材料。通过X射线粉末衍射仪（XRD）、傅里叶红外光谱仪（FT-IR）、扫描电子显微镜（SEM）等表征方法,分析了复合材料的物相和形貌。根据朗伯比尔定律,采用傅里叶红外光谱仪的KBr压片法测试并计算了各材料在2.5~25 μm区间的红外消光系数,并且研究了焙烧温度对材料消光性能的影响。研究结果表明:炭基/锌掺杂铁氧体前驱体焙烧后生成的炭基/锌掺杂铁磁体复合材料的红外消光性能均有所增强,经过700 ℃焙烧后的炭/钴锌铁磁体红外消光系数最大,为0.25 m2/g,具有较好的红外消光性能。     

The Structural Design,Simulation Analysis and Parameter Optimization of the Cheetah Robot’s Lumbar Vertebrae

The quality of skeleton system for the cheetah robot goes hand in hand with its bionic result of its shape, structure and functions. In view of the skeleton system constitution and structural characteristic of the cheetah, the team applied structure design, stimulation analysis and parameter optimization to developing the cheetah robot. In addition, after the invention of cheetah robot＇s anterior lumbar vertebra based on its functional attribute and connectivity attribute, the Solidworks Simulation was utilized to analyze the design, according to which improvement on the lumbar vertebra was made. Plus, the advantages of the CAD and CAE made the high efficiency of design work and high quality of the cheetah robot possible.     

A scaled thickness conditioning for solid- and solid-shell discretizations of thin-walled structures

The numerical discretization of thin shell structures yields ill-conditioned stiffness matrices due to an inherent large eigenvalue spectrum. Finite element parametrization that depends on shell thickness, like relative displacement shells, solid shells and other solid finite elements even add to the ill-conditioning by introducing high eigenmodes.To overcome this numerical issue we present a scaled thickness conditioning (STC) approach, a mechanically motivated preconditioner for thin-walled structures discretized with continuum based element formulations. The proposed approach is motivated by the scaled director conditioning (SDC) method for relative displacement shell elements. In contrast to SDC, the novel STC approach yields a preconditioner for the effective linear system. It is applicable independently of element technology employed, coupling to other physical fields, boundary conditions applied and additional algebraic constraints and can be easily extended to multilayer shell formulations.The effect of the proposed preconditioner on the conditioning of the effective stiffness matrix and its eigenvalue spectrum is studied. It is shown that the condition number of the modified system becomes almost independent from the aspect ratio of the employed elements. The improved conditioning has a positive influence on the convergence behavior of iterative linear solvers. In particular, in combination with algebraic multigrid preconditioners the number of iterations could be decreased by more than 85% for some examples and the computation time could be reduced by about 60%.