乘用车H臂悬架C特性的稳健性优化设计

针对某乘用车底盘调校过程中反复修改H臂悬架衬套参数所存在的调校周期长、性能改进不明显等问题,考虑到悬架安装误差,提出基于田口法的稳健性优化方案。首先建立悬架模型,根据KC试验数据验证模型准确性;对衬套刚度进行灵敏度分析,筛选主要影响因素,确定目标函数,通过正交试验设计对H臂悬架C特性进行多目标稳健性优化。结果表明:优化后的悬架C特性及其稳健性均有明显改进,且缩短了调校周期。     

汽车液压减振器抗异响稳健性设计

通过减振器台架试验对某双筒液压减振器仿真模型进行了置信度检验。以能表征异响程度的杆端加速度时域峰、谷值绝对值之和为目标函数,基于高精度仿真模型对19个设计参数进行了灵敏度及影响规律分析,在此基础上对灵敏度较大的11个参数进行了稳健设计,得到了信噪比最大、稳健性最好的最优参数组合。应用方差分析区分了设计参数对信噪比的显著程度,进一步调整对信噪比不显著但对目标函数较敏感的参数取值,最后通过台架试验进一步确认了最优方案,为其他类型减振器抗异响设计提供参考。     

数控机床空间误差球杆仪识别和补偿

提出了多轴机床空间误差的球杆仪识别方法和补偿技术。建立了机床刀尖相对工件的空间误差的误差参数模型;给出了在机床工作空间中三个互相垂直的平面内,用球杆仪测量圆周运动的半径误差结合机床的空间误差模型识别定位、直线度、角度、垂直度和反向间隙等误差参数的方法。补偿试验结果证明该误差识别与补偿方法省时有效。     

螺旋锥齿轮数控磨齿机机床空间误差与机床调整参数的关系

为求得对各项机床调整参数影响较大的机床空间误差,分析螺旋锥齿轮加工过程中数控机床空间误差物理涵义,并建立七轴五联动数控磨齿机床空间误差模型.基于齐次变换矩阵方法建立机床空间误差与机床调整参数之间的几何等量关系,推导出两者间的关联函数并进行分析.通过实例分析,发现对机床刀位调整值影响较大的机床空间误差主要是三直线轴垂直度误差和x轴沿Z向垂直度误差;对机床轮位调整值影响较明显的机床空间误差为z轴、B轴沿x向直线度误差以及A轴的安装距误差.为机床调整参数优化及螺旋锥齿轮几何误差补偿提供了理论依据.     

基于响应曲面法与满意度函数的柔顺机构多响应稳健参数设计

针对微指针放大柔顺机构在进行作业测量时,其柔性铰链部件在受到外界变载荷作用下柔度存在不稳定的实际情况,引入基于响应曲面法与满意度函数的多响应稳健参数优化设计。首先构建微指针放大柔顺机构的柔性铰链稳健参数设计模型,运用Minitab的中心复合有界设计模块对模型进行试验设计,获取试验数据;进而利用响应曲面法对试验数据进行分析,得到各显著性因子项,并对各响应值进行模型拟合;其次对拟合响应曲面模型的精度进行检验;最后采用满意度函数法,将多响应问题转变为求复合满意度函数加权几何平均值最大化的单响应问题,进而得到多响应稳健参数设计的最优方案。案例表明,该方法能够实现提高柔性铰链稳健性与精确性的目标,为柔性铰链的稳健参数设计提供了新的解决方案。     

基于不确定性定位参数与转向机构稳健设计

车辆定位参数与转向机构在设计过程中,存在诸多不确定性因素,这些将影响机构性能的稳健性。基于ADAMS与i SIGHT搭建基于随机不确定性的定位参数与转向机构的稳健设计模型,采用正交试验方法得到各优化目标的主要因素及各因素之间的交叉影响关系,依据试验数据建立优化目标与设计变量之间的二阶响应面近似模型。综合考虑定位参数、转向梯形机构的尺寸误差、安装误差等随机不确定性因素,应用田口方法建立了定位参数和转向梯形机构的稳健设计模型,并通过与传统设计方法的对比验证了田口方法的稳健性。应用蒙特卡洛法保证了转向过程中转向轮转角的精度,应用可靠性优化方法保证了转向机构传动角约束的可靠性。     

非线性机械系统分析性稳健设计

提出非线性条件下系统功能需求与结构特征参数、设计参数以及不可控因素之间的关系模型,按照该模型对系统敏感性进行了分析,给出系统敏感性指数 具体的数学表达式。按照稳健设计的基本思想,建立分析性稳健设计的优化模型,根据该优化模型结合TAGUCHI稳健性设计方法对系统稳健性实现的内在本质从理论上做出分析。基于各因素(系统结构特性、设计参数以及不可控因素)对系统稳健性影响程度的分析,提出稳健灵敏性矩阵RS。研究发现,在非线性条件下,系统本身的结构特性、设计参数以及外在的不可控因素与系统敏感性之间存在着直接的函数关系,并且它们均以各自不同的形式影响着系统的稳健性。系统本身的结构特性决定了设计参数对系统功能目标的作用形式,从而对系统功能目标的分布产生影响。设计参数的不同选择对系统稳健性影响的实质在于利用系统的非线性效应,以使设计功能靠近目标值,并使得变异达到最小。如果在合理的结构设计以及适当设计参数的选取仍然达不到系统稳健性要求的条件下,对不可控因素的控制则是一种从源头减小功能目标变动以提高系统稳健性的有效途径。     

系统性能稳健偏差与多点稳健设计优化

提出性能稳健偏差估计和自动多点寻优的稳健设计优化方法。该方法不要求系统参数的分布函数已知,且可适用于系统性能函数不能或不便求导和大偏差参数情况。应用设计敏感区理论和最坏情况分析原理,基于系统性能偏差和相应设计敏感区之间的关系,提出系统性能稳健偏差概念和多点稳健设计优化策略。稳健设计优化包括三个循环：内循环中,性能函数作为优化目标,性能目标的稳健性指数作为约束条件的判据,搜索优化设计方案;中循环中,由稳健性指数迭代,搜索求解系统性能目标的稳健偏差;外循环中,自动调整约束条件中设计稳健性判据的稳健性指数的门槛值,搜索可能存在的多个优化设计方案。理论分析和计算实例说明了该方法具有以下优点：能根据设计问题自动搜索可能存在的多个优化设计方案,可避免因要求选择合适的稳健性指数门槛值而给设计者带来的困难;不但能给出优化设计及优化目标值,而且能给出优化目标值的稳健偏差,为设计者在目标值及其稳健性之间决策提供重要依据。     

基于田口方法的某航空应急推动机构参数优化

利用田口方法的正交表对某航空应急推动机构试验方案进行设计,在试验数据基础上分析信噪比和贡献率,通过统计的方法优选出最佳的参数组合,并利用数值计算对优选方案进行验证.结果表明:得到的结论与参数影响机理分析的结果基本一致,采用双筒三节、压实装药是推动机构的最佳设计方式.该研究对于航空应急推动机构的稳健性设计具有一定的借鉴作用.     

VTM100型五轴加工中心空间误差检测及补偿研究

基于VTM100型五轴车铣复合加工中心的结构及其运动链构型特点,设计了误差检测方案,同时提出了加工中心空间误差补偿策略以及几何误差和热误差综合补偿模型。利用对角空间误差检测数实施了空间误差补偿,补偿后误差降低的幅度为11.87~50.8μm,精度提高了31.58%~81.77%。     

五轴数控机床万能主轴头空间误差建模研究

五轴机床万能主轴头空间误差建模的传统方法采用齐次变换矩阵(HTM)进行运算,计算过程复杂,物理意义很难理解。提出了一种主轴头空间误差的简化建模方法。综合考虑了主轴头两个旋转轴的运动误差和刀具热误差对主轴头空间精度造成的影响。优化了机床运动坐标系设置,从而降低了空间误差模型的复杂性。基于刚体运动学原理,描述了主轴头的运动误差传递关系。结合实例,推导出了主轴头空间误差的数学表达式,其建模过程简单,物理意义明确。     

Proposition for a Volumetric Error Model Considering Backlash in Machine Tools

This paper proposes a new scheme for evaluating the machine tool volumetric error model including the backlash error. The effects of backlash errors are assessed by experiments, conducted on a three-axis vertical-type machining centre. The assessment was taken for 18 error components out of the 21 geometric errors of a machine tool. It was shown that the backlash error of a machine tool is one of the systematic errors. Some important characteristics of the backlash error were identified; that is, the backlash error is a function of position, it decreases as the feedrate increases, and its size and shape vary according to the machine structure.     

Five axis machine tool volumetric error prediction through an indirect estimation of intra- and inter-axis error parameters by probing facets on a scale enriched uncalibrated indigenous artefact

The volumetric accuracy of five-axis machine tools is affected by intra-axis geometric errors (error motions) and inter-axis geometric errors (axes relative position and orientation errors). Self-probing of uncalibrated facets on the existing machine tool table is proposed to provide the necessary data for the self-calibration of the machine error parameters and of the artefact geometry using an indirect approach. A set of 86 non-confounded coefficients are selected from the ordinary cubic polynomials used to model both the intra- and inter-axis errors. A scale bar is added to provide the isotropic scale factor. The estimated model is then used to predict the actual tool to workpiece position. Experimental trials are conducted on a five-axis horizontal machining centre using its original unmodified machine table as an artefact. For validation purposes only, the estimated artefact geometry is compared to accurate coordinate measuring machine (CMM) measurements. A study of the volumetric error predictive capability of the model for selected subsets of estimated error coefficients is also conducted.     

Error analysis and compensation for the volumetric errors of a vertical machining centre using a hemispherical helix ball bar test

Machining accuracy is directly influenced by the quasi-static errors of a machine tool. Since machine errors have a direct effect upon both the surface finish and geometric shape of the finished workpiece, it is imperative to measure the machine errors and to compensate for them. A laser measurement system to identify geometric errors of a machine tool has disadvantages, such as a high cost, a long calibration time and the usage of a volumetric error synthesis model. In this study, we proposed a novel analysis of the geometric errors of a machine tool using a ball bar test without using a complicated error synthesis model. Also, a statistical analysis method was employed to derive geometric errors using a hemispherical helix ball bar test. According to the experimental result, we observed that geometric errors of the vertical machining centre were compensated by 88%.     

基于敏感度分析的机床关键性几何误差源识别方法

零部件几何误差耦合而成的机床空间误差是影响其加工精度的主要原因,如何确定各零部件几何误差对加工精度的影响程度从而经济合理地分配机床零部件的几何精度是目前机床设计所面临的一个难题。基于多体系统理论,在敏感度分析的基础上提出一种识别关键性几何误差源参数的新方法。以一台四轴精密卧式加工中心为例,基于多体系统理论构建加工中心的精度模型,并利用矩阵微分法建立四轴数控机床误差敏感度分析的数学模型,通过计算与分析误差敏感度系数,最终识别出影响机床加工精度的关键性几何误差。计算和试验分析表明,该方法可以有效地识别出对机床综合空间误差影响较大的主要零部件几何误差因素,从而为合理经济地提高机床的精度提供重要的理论依据。     

Kinematic errors identification of three-axis machine tools based on machined work pieces

Evaluating machine tool performance under machining conditions is generally used as the final test in machine tool industry. The seventh part of ISO-10791 describes a machining test using the accuracy of a finished work piece to determine the accuracy of three-axis machine tools. However the kinematic errors cannot be distinguished from each other by means of these test pieces. In this paper a new method to identify the kinematic errors of three-axis machine tool is proposed. A set of test pieces are designed where the kinematic errors of a machine tool can be measured separately along X, Y and Z directions. A volumetric error model is also presented based on the measured errors. This method is initially evaluated in virtual environment and then with some test pieces designed for this purpose. The results are compared with the laser interferometry measurements. It is shown that the measured positioning and straightness errors are consistent with the laser interferometry results. Angular errors measured by the test pieces are also complied with the laser interferometry results as long as the angular error magnitudes are large enough.     

Mechanical model of errors of probes for numerical controlled machine tools

CNC machine tool probes are not only used to set up the workpiece before machining and to control it after machining, but also to determine volumetric errors of the machine tool. That’s why there is a necessity not only for knowledge of the complete on-machine measurement system errors, but also for the knowledge about probe’s errors in separation from machine tools. This paper presents a theoretical model of errors of probes for CNC machine tools. It takes into account such unique features of the machine tool probes as the transducer with support on the whole circumference and as wireless communication. 3 probes: RMP60, MP700 and IRP32.00-MINI were tested using moving master artifact method, out of machine tool, to verify the model described. The triggering radius values obtained experimentally were compared with values calculated using theoretical model, resulting with a compliance up to 92%.     

Volumetric error modeling and sensitivity analysis for designing a five-axis ultra-precision machine tool

The five-axis machine tools are increasingly popular for meeting the demand of machining the workpiece with growing geometric complexity and high accuracy. This paper studies the volumetric error modeling and its sensitivity analysis for the purpose of machine design. The volumetric error model of a five-axis machine tool with the configuration of RTTTR is established based on rigid body kinematics and homogeneous transformation matrix, in which 37 error components are involved. The sensitivity analysis of volumetric error regarding 37 error components is carried out respectively. The analysis results are successfully used for the accuracy design and manufacture of a five-axis ultra-precision machine tool. The preliminary experiment of machining sine grid surface testifies the high accuracy and effectiveness of the designed five-axis machine tool.     

基于CNN-GRU组合神经网络的数控机床进给系统热误差研究

热变形引起的误差是影响数控机床精度的主要因素之一。为了减小热误差对数控机床精度的影响,提出一种基于CNN-GRU组合神经网络的热误差预测方法。通过热误差实验,采集螺旋曲面专用数控机床直线进给系统的温升数据和热误差数据;利用模糊C均值聚类和灰色关联度分析筛选进给系统温度敏感点;以温度敏感点的温升数据和进给系统热误差为数据样本,建立CNN-GRU热误差预测模型。为验证模型的准确性和实用性,与基于CNN-LSTM和基于LSTM的传统热误差预测模型进行预测对比分析,结果表明CNN-GRU模型预测结果的平均绝对误差、均方根误差和决定系数均优于CNN-LSTM模型和LSTM模型,具有较高的预测精度和鲁棒性。提供的热误差模型可为后续误差补偿奠定基础,为数控机床的热误差预测提供思路。     

A new approach to thermally induced volumetric error compensation

A traditional model for thermally induced volumetric error of a three-axis machine tool requires measurement of 21 geometric error components and their variation data at different temperatures. Collecting these data is difficult and time consuming. This paper describes the development of a new model for calculating thermally induced volumetric error based on the variation of three error components only. The considered error components are the three axial positioning errors of a machine tool. They are modelled as functions of ball-screw nut temperature and travel distance to predict positioning errors when the thermal condition of the machine tool has changed due to continuous usage. It is assumed that the other 18 error components remain identical to the pre-calibrated cold start values. This assumption is justified by the fact that the machine tool’s thermal status significantly affects three axial positioning errors that dominate machining errors for a machine tool after its continuous use. To demonstrate the effectiveness of the proposed model two types of machining jobs, milling and drilling, on a three-axis horizontal CNC machining centre are simulated and the machined part profiles are predicted. The results show that the thermally induced volumetric error was reduced from 115.40 to 45.37?μm for the milled surface, and the maximum distance error between drilled holes for the drilling operation was reduced from 38.69 to ?0.14?μm after compensation.