基于灰色线性回归组合模型的机床热误差建模方法

为了控制机床热误差和提高机床加工精度,考虑到测得的热误差数据同时存在着线性和非线性因素,提出了采用具有处理线性和非线性能力的灰色线性回归组合热误差模型的建模方法.用此方法对某卧式加工中心热误差进行了建模和预测,并引入BP神经网络对热误差模型的残差进行修正,从而获得了比较准确的热误差预测值.与用指数函数来模拟生成数据的灰色模型所获得的预测值进行了比较,证明了灰色线性回归组合及BP神经网络模型在机床热误差补偿建模应用中的优越性.     

基于CSO-SVM的数控机床主轴热误差建模

针对数控机床多热源所致的温升与主轴热误差之间复杂的非线性关系问题,提出一种鸡群优化（chicken swarm optimization, CSO）算法与支持向量机（support vector machines, SVM）相结合的主轴热误差预测模型（以下简称热误差模型）。以某精密数控机床的主轴单元为研究对象,采用五点法对其在空转状态下的轴向热变形进行测量,并借助热电偶传感器对机床的4个关键温度测点的温度进行采集。以SVM为理论基础,随机选取75%的数据样本进行训练,进而构建主轴热误差模型。其中,利用CSO算法优化SVM模型的惩罚参数c和核参数g,以提升热误差模型的预测能力及鲁棒性。以余下的25%的样本作为测试数据集,对所得热误差模型进行验证。利用CSO-SVM模型对不同工况下主轴的热误差进行预测,并将预测结果与测量结果进行对比。结果表明：当主轴转速为3 000 r/min时,CSO-SVM模型的平均预测精度高达97.32%,相较于多元线性回归模型和基于粒子群优化的SVM模型分别提升了6.53%和4.68%;当主轴转速为2 000, 4 000 r/min时,CSO-SVM模型的平均预测精度分别为92.53%、91.82%,表明该模型具有较高的预测能力和良好的鲁棒性。CSO-SVM模型具有较强的实用性和工程应用价值。     

考虑结构热变形的机床进给系统热误差研究

为系统研究精密机床进给系统热误差的形成机理及其影响因素，提出了一种考虑结构热变形的进给系统热误差建模方法。在考虑进给系统内生热源及冷却系统对丝杠螺母副的温升和丝杠热变形作用机制的前提下，同时考虑了进给系统内生热源对精密机床结构大件（床身、立柱、溜板）热态特性的影响规律。通过分析结构热变形引起的进给系统电机座和轴承座相对位置的变化，建立了综合考虑结构大件和丝杠热变形的进给系统热误差模型。以JIG630精密卧式加工中心为例，进行了考虑结构热变形和不考虑结构热变形的进给系统热误差建模与仿真分析，并开展了相应的测试验证实验。结果表明考虑结构热变形的进给系统热误差模型仿真值与实验结果具有更高的一致性。该建模方法对精密机床进给系统热平衡设计、热误差的控制与补偿具有重要参考意义。     

自回归分布滞后模型在数控机床热误差建模中的应用

对多元线性回归模型、回归与残差AR叠合模型和自回归分布滞后模型3种热误差建模方法进行了介绍与比对分析。多元线性回归模型方法简单快捷,但因热误差呈非线性且具有互交作用,较难获得精确热误差数学模型。后两个模型均属时间序列分析方法,其优点是能够比较精确地建立热误差数学模型,两者的区别是叠合模型把参数估计分成两部分,而自回归分布滞后模型是统一估计参数,因此叠合模型的精度要低于自回归分布滞后模型精度,并通过实例验证,自回归分布滞后模型在精密数控机床热误差建模中具有较好的建模精度。     

基于表面测温的关节轴承外圈加工热变形预测

针对关节轴承外圈加工热变形误差,本文基于多元线性回归原理建立了一套热变形误差预测模型。首先利用有限元仿真获得工件加工表面热变形与温度场数据,然后在此基础上利用多元线性回归方法建立工件表面加工节点热变形与选取的表面测温点之间的数学关系。此模型可有效消除加工过程中切削参数调整与边界条件不准确对热变形计算结果的影响。     

数控机床热误差的建模与预补偿

研究了数控机床热误差的预补偿方法。建立了基于主轴转速的热误差自回归模型,从而不需要测量机床的温度场就可以预测热误差。在加工前通过修改工作的数控加工程度即可进行补偿,大大简化了误差补偿过程。可应用于中等精度的数控机床。     

进给系统热变形对机床运动重复性误差的影响研究

为了分析进给系统热变形对机床运动重复性误差的影响，提出了一种基于分层模型-移动热源的进给系统热变形建模方法。将进给系统分为丝杠层和工作台层，将移动结合面等效为弹簧。采用实体单元和接触单元建立了有限元模型，在丝杠和导轨上施加移动热源，获得进给系统的温度场和热变形。在此基础上，分析了工作台进给速度、轴承预紧力矩和滑块支撑距离对机床运动重复性误差的影响，并进行了实验验证。研究表明，工作台进给速度和轴承预紧力距对机床运动重复性误差的影响较大，滑块支撑距离对机床运动重复性误差的影响较小。研究结果为在机床设计和装配中减小机床运动重复性误差提供了依据。     

基于BP神经网络模型的MEMS加速度计误差补偿方法

现阶段普遍采用多元线性回归对加速度计误差建模,并利用最小二乘法对模型参数辨识,但其对加速度计精度提高有限,因此该文提出一种基于BP神经网络模型的MEMS加速度计误差补偿方法。该方法利用BP神经网络建立加速度计误差模型,通过多位置翻滚进行实验数据测量,并对模型进行训练,最后利用训练好的模型对加速度计误差进行补偿。比较多元线性回归和BP神经网络建模对加速计误差补偿结果,其标准偏差分别为0.001 9 g和0.000 16 g。结果表明误差下降一个数量级,说明BP神经网络能有效地补偿加速度计误差。     

精密车削中心热误差和切削力误差综合建模

热误差和切削力误差是影响数控机床精度的最重要的两个误差源,误差补偿技术是一种消除机床误差经济有效的方法,而有效的误差补偿依赖于准确的误差模型。在对切削加工过程中的热变形和切削力分析的基础上,选取合理的参量,采用BP神经网络和PSO算法相结合的优化方法建立了热误差和切削力综合模型。BP-PSO建模方法改善了网络模型的收敛速度和预测精度。基于所建误差模型,对一台精密车削中心加工实时补偿后使得径向加工误差从27μm提高到8μm,大大提高了车削加工中心的加工精度,验证了模型精度。     

基于热压缩的Cu-15Ni-8Sn合金动态再结晶行为研究

目的 获得Cu-15Ni-8Sn合金动态再结晶临界模型,描述热变形参数对动态再结晶晶粒尺寸的影响规律.方法 基于前期通过Gleeble-3500热模拟机得到的热压缩实验数据,分析Cu-15Ni-8Sn合金在不同热变形参数下的再结晶晶粒尺寸及流变应力数据,采用线性回归拟合等方式建立动态再结晶模型,并利用数值模拟与实验相结合的方法 验证模型精确度.结果 采用YADA模型描述Cu-15Ni-8Sn合金的动态再结晶,通过线性拟合求得模型参数C1=11895.554,C2=0.1503,C3=0.1553,C4=3.933×10?4,C5=2995.6409,数值模拟与实验所得的平均晶粒度分别为16.7μm和15.5μm.结论 变形温度和变形速率对Cu-15Ni-8Sn合金热变形中的再结晶过程有重要影响.变形温度越高,临界应变越小,越容易发生动态再结晶,动态再结晶晶粒尺寸越大;应变速率越小,动态再结晶晶粒尺寸越大.研究所构建的Cu-15Ni-8Sn合金动态再结晶临界模型具有较高精度,将为后续该合金热塑性变形工艺设定提供理论基础.     

Interpretation of the thermal curve in differential thermal analysis

On the basis of an analysis of the heat transfer between samples and the surrounding medium, principles are formulated for the correct interpretation of the thermal curves in DTA. The influence of the type of phase transformation and the test conditions on the form of the thermal curve is shown.Translated from Inzhenerno-Fizicheskii Zhurnal, Vol. 36, No. 3, pp. 480–486, March, 1979.     

Measurements of the thermal gradient over EB-PVD thermal barrier coatings

Conventional two-layered structure thermal barrier coatings (TBCs), graded thermal barrier coatings (GTBCs) and graded thermal barrier coatings with micropores were prepared onto superalloy DZ22 tube by electron beam physical vapor deposition (EB-PVD). Thermal gradient of the TBCs was evaluated by embedding two thermal couples in the surfaces of the tube and the top coat at different surrounding temperatures with and without cooling gas flowing through the tube. The results showed that higher thermal gradient could be achieved for the GTBCs with micropores compared to the two-layered structure TBCs and GTBCs. However, after the samples were heated at 1050°C, the thermal gradient for the GTBCs with or without micropores decreased with the increase of heating time. On the other hand, the thermal gradient for the TBCs increased with the increase of heating time. Cross-section observations by scanning electron microscopy showed that the change in microstructure was the main reason for the change of the thermal gradient.     

On the thermal expansion of composite materials and cross-property connection between thermal expansion and thermal conductivity

The paper focuses on the quantitative characterization of heterogeneous microstructures from the point of view of the material’s thermal expansion. First, we derive expression for the second rank thermal expansion contribution tensor of an inhomogeneity and specify it for various inhomogeneity shapes. Case of a spheroidal inhomogeneity in an isotropic material is discussed in detail. Thermal expansion contribution tensor is used as a basic building block to calculate effective thermal expansion of a heterogeneous material and to derive explicit cross-property connection between thermal expansion and thermal resistivity of a composite. We compare our results with experimental data available in literature and with other approaches.     

Effect of thermal coarsening on the thermal conductivity of nanoporous gold

The thermal conductivities of nanoporous gold (NPG) microwires annealed at different temperatures have been measured in the temperature range from 100 to 320 K. Considering the electron-surface scattering, the thermal conductivity is expected to increase with the increase of ligament diameter. However, the thermal conductivity of NPG microwire is found to decrease after thermal coarsening, and has a maximum value at around 250 K for the as-dealloyed sample. We suggest that the defects accumulating at a relatively high temperature and the reduction in defect spacing may cause these temperature behaviors of thermal conductivity. Taking into account the electron scattering on ligament surfaces and defects, a modified theoretical model for the thermal conductivity of nanoporous metal is proposed to agree with our experimental results.     

Simultaneous measurement of the thermal conductivity and thermal diffusivity of liquids

In theory, the hot-wire technique for measuring the thermal conductivity of liquids can be used simultaneously to determine the thermal diffusivity. In practice, however, the latter property has so far been determined only with moderate accuracy because of (a) inaccurate bridge balancing due to drift problems, (b) parasitic capacities that delay the heating, and (c) poor precision in the determination of the time. A new measurement procedure has been developed which features (a) a short measuring time, (b) a reduced significance of the balancing technique, (c) a good reproducibility, and (d) a low sensitivity to most error sources. Thermal conductivity and thermal diffusivity results using this procedure, for toluene and n-heptane, which are the generally accepted standards for thermal conductivity, are presented and compared with results from other sources.     

Accurate measurement of the thermal conductivity and thermal diffusivity of toluene andn-heptane

Accurate and simultaneous measurements of the thermal conductivity and thermal diffusivity of toluene andn-heptane were made with an improved transient hot-wire method by using a transfer function having a feedback loop, in the temperature range of 0 to 45°C at atmospheric pressure. The accuracy of the empirical equations as a function of temperature is estimated to be 0.4 to 0.5% for the thermal conductivity and about 4% for the thermal diffusivity. Paper presented at the Fourth Asian Thermophysical Properties Conference, September 5–8, 1995, Tokyo, Japan.     

Measurement of the thermal diffusivity by the thermal wave method using low-power heat sources

The errors in measuring the thermal diffusivity by the plane thermal wave method are considered as a function of the thermal flux power density. The minimum values of the thermal flux power density required for measurements with a specified error and the optimum parameters of the samples and of the heat source are determined. __________ Translated from Izmeritel’naya Tekhnika, No. 8, pp. 44–46, August, 2007.     

Measurement of thermal diffusivity of diamond by the light-induced thermal lattice method

The thermal diffusivity coefficient of natural diamonds is measured by optical induction of thermal diffraction lattices.Notation gc thermal conductivity coefficient - thermal diffusivity coefficient - diffraction efficiency - I_dif diffracted radiation intensity - I_Probe probe radiation intensity - probe radiation wavelength - c specific heat - Q surface energy density - thermal lattice relaxation time - thermal lattice period Translated from Inzhenerno-Fizicheskii Zhurnal, Vol. 56, No. 5, pp. 745–748, May, 1989.