数控机床加工精度分析和提高方法要求

该文探讨数控机床加工精度分析及其提高方法要求。通过列举数控机床加工实例,探讨加工过程中影响机床加工精度的因素,分析问题产生原因,并提出促进精度提高的对策。根据误差类型的不同,分别辅以误差补偿、误差建模、误差测量及误差防止措施,有效降低了误差水平。结果表明,明确数控机床加工精度问题产生原因,选取适配的误差补偿方案,能有效提升数控机床加工精度。     

数控机床热误差智能补偿系统设计与研究

数控机床热变形误差影响加工精度的40%～70%且目前未能得到改善。参考机床热误差补偿研究后设计了温度检测系统,该系统采用无线传输技术,根据采集数据建立了一套相适应的误差模型,发现存在热变形误差后立即进行补偿处理来确保误差最小化。此外,该系统弥补了温度有线检测的不足,确保了数据获取的完整性与准确性,实现了高效、准时地误差补偿。     

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。     

三坐标数控机床精度检测与误差补偿

介绍了利用激光干涉仪检测和辨识数控机床几何精度的方法,建立了基于激光干涉仪的三坐标数控机床几何误差的数学模型．在准确掌握三坐标数控机床几何误差的基础上,利用所开发的误差补偿软件进行了误差补偿实验．结果表明,经过误差补偿,数控机床的加工精度可以明显提高．     

数控机床误差测量方法研究

分析了数控机床误差源,在此基础上对数控机床几何误差和主轴热变形误差的测量方法进行研究。该误差测量方法在机床工业研究中具有广泛的应用范围和通用性,对进一步提高数控机床的加工精度具有重要的研究意义。     

数控机床几何误差补偿方法应用研究

本文介绍了数控机床几何误差的来源,分析了数控机床几何误差的补偿途径,简要地介绍了两种数控机床几何误差模型,并应用两种几何误差模型分别补偿几何误差,测量并分析比较补偿结果。     

基于图像反馈的CNG车载瓶底加工刀具路径误差补偿技术

CNG车载瓶底部加工质量直接影响CNG车载瓶的安全运行.针对传统开放式数控机床的进刀方式造成加工原理误差,工件加工时的安装误差导致瓶底强度削弱等技术问题,将基于图像反馈的刀具路径误差补偿技术应用于CNG车载瓶底部加工组合机床的控制系统,构建基于图像反馈的模型,阐述了CNG车载瓶底加工刀具路径误差识别与补偿设计的算法和流...     

数控机床的误差补偿的实现

随着数控机床的发展,它的精度问题也随之受到关注。近年来,随着我国数控机床关键技术的突破,开始关注数控机床的性能,数控机床精度的研究受到重视。误差补偿法是人为地造出一种新的误差去抵消当前成为问题的原始误差,是一种既有效又经济的提高机床加工精度手段,其工程意义是非常显著的。对数控机床的误差补偿的实现进行研究。     

数控机床运动误差的测试装置——双球规测量仪

本文介绍了作者设计的双球规测量仪的结构与工作原理。使用这种装置不仅可以测量出数控机床的运动误差，而且可以通过误差矢量的计算，找出造成误差的主要原因，计算出误差的大小和方位，并通过软件给予补偿，使数控机床加工精度得到提高。     

专用数控机床中的工件定位误差自动补偿技术

专用数控机床由于能够较好地满足大批量、高效率、高精度生产的需求而在现代加工领域中获得了广泛的应用。工件定位误差自动补偿技术是其高效率、高精度生产的重要保证，本文讨论了专用数控机床中的工件定位误差自动补偿技术及其实现方法，并介绍了该技术的一个应用实例。     

基于单光束干涉仪的机床主轴热误差实时测量

主轴热误差是数控机床的主要热误差源,本提出了一种使用三路单光束干涉仪（SBI3）进行机床主轴热误码差的非接触式实时测量方法。可以快速准确地测量主轴热误差。实验结果表明,所测立式加工中心主轴热误差沿Z轴方向最大,约为50μm,测量误差约为1.0μm。     

带冷却系统的XK717数控铣床主轴部件热特性分析

机床主轴系统是机床的核心部件，其热特性的好坏，直接影响机床的加工精度；以建立主轴系统的有限元模型，结合主轴系统与普通水箱之间的冷却模型，对带有冷却套的主轴系统进行了热特性分析，得出了主轴系统的热特性曲线；根据分析结果，对XK717数控铣床主轴部件冷却套的布局进行了改进设计，为优化数控铣床主轴系统提供了理论依据。     

Study on the thermally inducedspindle angular errors of a five-axis CNC machine tool

Thermally induced spindle angular errors of a machine tool are important factors that affect the machining accuracy of parts. It is critical to develop models with good generalization abilities to control these angular thermal errors. However, the current studies mainly focus on the modeling of linear thermal errors, and an angular thermal error model applicable to different working conditions has rarely been investigated. Furthermore, the formation mechanism of the angular thermal error remains to be studied. In this study, an analytical modeling method was proposed by analyzing the formation and propagation chain of the spindle angular thermal errors of a five-axis computer numerical control (CNC) machine tool. The effects of the machine tool structure and position were considered in the modeling process. The angular thermal error equations were obtained by analyzing the spatial thermoelastic deformation states. An analytical model of the spindle angular thermal error was established based on the geometric relation between thermal deformations. The model parameters were identified using the trust region least squares method. The results showed that the proposed analytical model exhibited good generalization ability in predicting spindle pitch angular thermal errors under different working conditions with variable spindle rotational speeds, spindle positions, and environmental temperatures in different seasons. The average mean absolute error (MAE), root mean square error (RMSE) and R² in twelve different experiments were 4.7 μrad, 5.6 μrad and 0.95, respectively. This study provides an effective method for revealing the formation mechanism and controlling the spindle angular thermal errors of a CNC machine tool. The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-022-00409-x     

基于有限元方法的数控铣床整机热特性分析

使用有限元方法,对新设计的XK717数控铣床进行了整机热特性分析,并与XK510数控铣床 (成熟产品)的分析结果进行比较,根据比较结果,找出XK717数控铣床热特性的薄弱部件,从而为提高XK717数控铣床的整机热特性指明了改进的方向.     

A control algorithm for improving the accuracy of five-axis machine tools

An algorithm for reducing the influence of geometrical, thermal, kinematic and stiffness errors in five-axis machine tool components on the desired tool position and orientation is given. This new algorithm is based on the calculation of the cutting tool error matrix for orthogonal machine tools. In the new model of this matrix, all angular errors of the machine links are considered as infinitesimal rotations. The error matrix is a function of the commanded machine component positions and the errors in these positions. To correct errors in the three translational and two angular tool positions, a matrix of commanded tool position and orientation is multiplied by the inverse error matrix in every period of the tool trajectory interpolation. This corrected matrix of the tool position and orientation provides the inverse kinematics used for calculation of the successive links positions required for achieving the given tool trajectory. The control algorithm for five-axis machine tools with the error compensation is implemented both in the CNC system and in the postprocessor. The proposed algorithm is applied on a vertical five-axis turning centre with two translational and three rotational axes. Twenty-four errors that could cause inaccurate machining are recognised on this machine. The machine links and their coordinate frames are denoted using the Denavit–Hartenberg parameters.     

Load spectra of CNC machine tools

Load spectra of CNC machine tools are described in this paper; 112 CNC machine tools have been traced for 3 years. Data including machining parameters and conditions, drawings and NC programs of parts, process cards and specifications of each individual CNC machine tool are gathered. A database containing this information is designed. The loads of CNC machine tools are calculated and the distribution parameters of loads are estimated. A fuzzy multicriteria comprehensive evaluation method is applied to evaluate the fitness of the distribution model. This methodology lays a foundation for the reliability designs of CNC machine tools. Copyright © 2000 John Wiley & Sons, Ltd.     

Modeling and identification of the multi-axis drive system using support vector machine and granular computing

Advanced manufacturing technology requires high-precision capability in multi-axis computer numerical control (CNC) machine tools. At present, the modeling and identification for the drive system of CNC machine tools has some defects. In order to solve the problem, some interdisciplinary theories and methods, such as support vector machines, granular computing, artificial immune algorithms, and particle swarm optimization algorithms, have been used to model and identify multi-axis drive systems for CNC machine tools. An identification method using a support vector machine, based on granular computing, is presented to identify a multi-axis servo drive system model for improving the precision of model identification, and an immune particle swarm optimization algorithm, based on crossover and mutation functions, is proposed to optimize the structure parameters of the support vector machine based on granular computing. The proposed identification method was evaluated by experiments using the multi-axis servo drive system. The experimental results showed that the proposed approach is capable of improving modeling and identification precision.     

基于元动作单元的数控机床故障分级决策方法

为快速、准确地判断数控机床故障等级,避免出现花大代价处理次要故障,而关键故障却被忽略的情况,提出了一种以元动作单元为分析主体的数控机床故障分级决策方法。首先,为细化数控机床故障分析的粒度,使得分析过程更加简便,从系统功能分解的角度将数控机床按照“功能（function）-运动（motion）-动作（action）”逐层分解直至元动作层。其次,通过对分解过程进行分析,给出了元动作单元概念模型,明确了一个标准元动作单元需要包含的3类要素。然后,从动作的层面全面分析并总结元动作单元的故障模式类型。接着,定义了元动作单元故障模式的3个等级,按照评价指标对数控机床故障模式进行评价,再通过灰色聚类理论分析故障模式量化评价值,利用所得出的聚类结果建立了故障模式分级的原始决策表,随后通过粗糙集理论对原始决策表进行知识约简以使决策规则进一步简化,最终形成了一种能够快速、准确确定故障模式等级的决策方法。最后,通过对某数控机床齿条移动元动作单元的分析,验证了所提方法的合理性与有效性。实例分析结果表明使用该方法能够快速、准确地确定数控机床的故障模式等级,提高了决策效率,所得结论更加明确且具有针对性,可为后续的维修过程控制提供依据。研究结果能给相关企业确定数控机床故障等级提供有效指导,一定程度上优化企业维修资源的配置。     

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。