STUDY ON NEW METHOD OF IDENTIFYING GEOMETRIC ERROR PARAMETERS FOR NC MACHINE TOOLS

The methods of identifying geometric error parameters for NC machine tools are introduced. According to analyzing and comparing the different methods, a new method-displacement method with 9 lines is developed based on the theories of the movement errors of multibody system (MBS). A lot of experiments are also made to obtain 21 terms geometric error parameters by using the error identification software based on the new method.

The Application of the GM(1,1) Metabolism Model to Error Data Processing of NC Machine Tools

This paper applied the gray system theory to error data processing of NCmachine tools according to the characteristic. It presented the gray metabolism model of error dataprocessing. The test method for the model needs less capacity. Practice proved that the method issimple, calculation is easy, and results are exact.

Geometric error measuring,modeling,and compensation for CNC machine tools:A review

Geometric error,mainly due to imperfect geometry and dimensions of machine components,is one of the major error sources of machine tools.Considering that geometric error has significant effects on the machining quality of manufactured parts,it has been a popular topic for academic and industrial research for many years.A great deal of research work has been carried out since the 1970s for solving the problem and improving the machining accuracy.Researchers have studied how to measure,detect,model,identify,reduce,and compensate the geometric errors.This paper presents a thorough review of the latest research activities and gives an overview of the state of the art in understanding changes in machine tool performance due to geometric errors.Recent advances in measuring the geometrical errors of machine tools are summarized,and different kinds of error identification methods of translational axes and rotation axes are illustrated respectively.Besides,volumetric geometric error modeling,tracing,and compensation techniques for five-axis machine tools are emphatically introduced.Finally,research challenges in order to improve the volumetric accuracy of machine tools are also highlighted.

3-PRS serial-parallel machine tool error calibration and parameter identification

3-PRS serial-parallel machine tool consists of a 3-degree-of-freedom (DOF) implementation platform and a 2-DOF X-Y platform. The error modeling and parameter identification methods were deduced based on 3-PRS serial-parallel machine tool. 3-PRS serial-parallel machine tool was researched, and the mechanism of error analysis, modeling, identification of error parameters and measurement equipment for the use of agency error of measurement were conducted. In order to achieve the geometric parameters calibration and error compensation of the serial-parallel machine tool, the nominal structural parameters of the controller was adjusted by identifying the structure of the machine tool. With the establishment of a vector space size chain, we can do the error analysis, error modeling, error measurement and error compensation can be done.

Bayesian networks modeling for thermal error of numerical control machine tools

The interaction between the heat source location, its intensity, thermal expansion coefficient, the machine system configuration and the running environment creates complex thermal behavior of a machine tool, and also makes thermal error prediction difficult. To address this issue, a novel prediction method for machine tool thermal error based on Bayesian networks (BNs) was presented. The method described causal relationships of factors inducing thermal deformation by graph theory and estimated the thermal error by Bayesian statistical techniques. Due to the effective combination of domain knowledge and sampled data, the BN method could adapt to the change of running state of machine, and obtain satisfactory prediction accuracy. Ex- periments on spindle thermal deformation were conducted to evaluate the modeling performance. Experimental results indicate that the BN method performs far better than the least squares (LS) analysis in terms of modeling estimation accuracy.

METHOD OF ENHANCING THE POSITIONING ACCURACY FOR NC MACHINE TOOLS

Based on the kinematics of the multi-body system , a general model for the positioning errors of NC machine tools by means of the lower numbered body array and the geometric constraint is presented. The parameters identification of geometric errors by an improved 22-line method is discussed. Moreover , an intelligent error compensation controller has been developed. All these are verified by a series of experiments on XH714 machining center. The results show that the prosition- ing errors with compensation have been reduced to ±7 μm from 50 μm.

MOTION ERROR ESTIMATION OF 5-AXIS MACHINING CENTER USING DBB METHOD

In order to estimate the motion errors of 5-axis machine center, the double ball bar （DBB） method is adopted to realize the diagnosis procedure. The motion error sources of rotary axes in 5-axis machining center comprise of the alignment error of rotary axes and the angular error due to various factors, e.g. the inclination of rotary axes. From sensitive viewpoints, each motion error is possible to have a particular sensitive direction in which deviation of DBB error trace arises from only some specific error sources. The model of the DBB error trace is established according to the spatial geometry theory. Accordingly, the sensitive direction of each motion error source is made clear through numerical simulation, which is used as the reference patterns for rotational error estimation. The estimation method is proposed to easily estimate the motion error sources of rotary axes in quantitative manner. To verify the proposed DBB method for rotational error estimation, the experimental tests are carried out on a 5-axis machining center M-400 （MORISEIKI）. The effect of the mismatch of the DBB is also studied to guarantee the estimation accuracy. From the experimental data, it is noted that the proposed estimation method for 5-axis machining center is feasible and effective.

Identification of the key thermal points on machine tools by grouping and optimizing variables

The grouping and optimization approach to identify the key thermal points on machine tools is studied.To solve the difficulty in grouping because of the high correlated variables from distinct groups,the variables grouping technique is improved.Temperature variables are sorted according to their relativities with the thermal errors.The representative temperature variables are determined by analyzing the variable correlation in sort order and removing the other variables in the same group.Considering the diverse effect of importing the different variables on thermal error model,the method of variable combination optimization is improved.Regression models made up of different combination of representative temperature variables are evaluated by the index of both the determined coefficient and the average residual squares to select the combination of the temperature variables.For the machine tools with complicated structures which need more initial temperature measuring points the improvement is demanded.The improved approach is applied to a precision horizontal machining center to identify the key thermal points.Experimental results show that the proposed approach is capable of avoiding the high correlation among the different groups' variables,effectively reducing the number of the key thermal points without depressing the prediction accuracy of the thermal error model for machine tools.

数控机床几何误差单轴五次测量与辨识方法

针对数控机床几何误差项的准确测量与辨识问题,提出了一种基于激光干涉仪的机床空间几何误差单轴五次测量与辨识方法。首先,针对X、Y、Z轴分别设置了一条测量线,测量了3条划定线上除滚转误差外的其他15项几何误差,共计15次测量;然后,分析了转角误差对直线度误差以及直线度误差对定位误差的耦合影响,并建立了误差辨识方程组;最后,根据误差辨识方程组,得到了机床21项几何误差;并进行了单轴五次测量法的测量和辨识实验,并将所得结果与空间九线法测量辨识结果进行了对比分析。研究结果表明:单轴五次测量法与空间九线法测量辨识结果的空间误差向量最大偏差为1.93μm,平均偏差为0.58μm,该结果验证了单轴五次测量法是准确和有效的。该方法考虑了实际测量过程中的误差耦合情况,因此相比于空间九线法,该方法减少了测量线数与测量次数,简化了误差项的求解过程;同时,采用单轴运动方式可以有效避免其他轴对当前运动轴误差的影响。

数控机床误差补偿技术及应用──NC型误差补偿控制器的开发

如何实现数控机床空间误差值的控制是误差补偿技术关键之一。文章介绍以单片机为核心的ＮＣ型误差补偿控制器，并在ＸＨ７１４立式加工中心和ＸＨＦＡ２４２０仿形定梁龙门加工中心上得以实现。该方法对在其他机床及开放型数控系统上应用补偿技术有其重要的参考意义。

NC机床运动误差的矢量分析法

提出了数控机床圆弧插补运动误差的矢量分析方法。可用双球规测量装置测得数控机床圆弧插补运动的综合误差。在分析运动误差与误差矢量关系的基础上以几种典型误差为例，从理论上提出了单一误差源数学模型的建立方法，给出了与单一误差源所对应的误差特征曲线。用这些数学模型和特征曲线可以诊断出数控机床圆弧插补误差产生的原因。

基于球杆仪的五轴数控机床误差快速检测方法

几何误差是五轴数控机床重要误差源,针对传统测量方法仪器昂贵、测量周期长问题,提出基于球杆仪的五轴数控机床几何误差快速检测方法。对于机床的平动轴误差,利用多体系统理论及齐次坐标变换法,建立平动轴空间误差模型,通过球杆仪在同一平面不同位置进行两次圆轨迹,辨识出4项平动轴关键线性误差;针对五轴机床的转台和摆动轴,设计基于球杆仪的多条空间测试轨迹,完整求解出旋转轴12项几何误差。实验结果显示,所提方法获得转角定位误差与激光干涉仪法最大误差为0.001 8°,利用检测结果进行机床空间误差补偿,测试轨迹偏差由16μm降至4μm,为补偿前的25%,验证了方法的有效性。提出的五轴机床几何误差检测方法方便、便捷,适用于工业现场。

基于机器人与机床联合工作的误差测量与解耦

工业机器人与数控机床联合工作在自动化生产及智能制造中发挥着重要作用。为了解决机器人与数控机床联合工作时产生的误差问题,在其联合工作的条件基础上建立了机器人与机床的综合误差模型,将机器人与数控机床分为两个运动支链。考虑到二者之间的相互关系,提出了一种利用机床测头进行联合误差测量的方法,通过对机器人和数控机床的联合运动进行测量,来获取系统的总体误差信息。针对数控机床运动支链的误差测量与辨识,采用NUBRS曲线作为机床的运动轨迹,在此基础上建立了数控机床几何误差辨识模型,该模型包含了27项误差元素。经过实验验证,在测量出机床与机器人联合工作所产生的空间误差后,有效辨识出数控机床4个坐标系共27项误差元素。

机床空间误差完备建模方法与NC代码优化补偿技术

空间误差是机床几何误差元素综合作用的结果,但现阶段空间误差模型大多存在缺失若干几何误差元素的问题,直接影响着机床空间误差的预测精度。为此,提出一种机床空间误差完备建模方法,以多体系统理论及齐次坐标变换为分析研究手段,在充分考虑体间坐标系初始位置关系及原始误差特征矩阵的基础上,确保模型包含机床全部几何误差元素。进而,针对传统基于NC代码的空间误差补偿技术中存在残差的局限性,提出将NC代码坐标的逆向叠加过程转化为最优化设计问题,并借助遗传算法对该问题进行求解计算,达到消除空间误差补偿残差的目的。最终,以某型卧式加工中心为研究对象进行计算分析与实验验证,结果表明:依据所提方法构建的空间误差完备模型包含加工中心全部21项几何误差元素,空间误差预测结果较精确;所提NC代码优化补偿技术使加工中心空间定位精度得到进一步提升,补偿后定位精度增幅最高达90.92%。研究成果可为数字制造装备精度问题探索提供较重要的理论与工程技术支撑。

Pro/NC刀路程序加工参数的自动设置

介绍了利用Pro/NC进行NC程序的自动编制所需要的环境配置。探索了加工参数的自动提取方法,并介绍了使用刀具库加载"切削数据"的优势和特点。

基于参数自适应的永磁同步电机无差拍预测电流控制

无差拍预测电流控制(dead-beat predictive current control,DPCC)因其响应迅速而在电机控制领域具有较大应用潜力,然而受参数敏感影响,该方法鲁棒性不高。为此,文中提出一种结合参数自适应的永磁同步电机(permanent magnet synchronous machine,PMSM)电流无差拍控制方法,以解决无差拍控制在参数失调下的鲁棒性问题。首先,介绍无差拍电流控制的基本原理。随后,重点分析在电机参数不精确的条件下,参数误差对无差拍电流控制环路的影响。针对电机参数不精确的情况,提出一种结合了参数自适应算法的预测电流控制方法,通过在线进行电机参数辨识,实时修改预测电流控制器的参数,以达到参数修正的效果。最后,对该方法的控制效果进行对比仿真验证与效果评估。结果表明,采用该方法后电流控制过程中系统鲁棒性提升明显,效果较好。

融合坐标系误差模型的工业机器人运动学标定

为解决辨识过程中MD-H误差模型不能完整描述机器人结构参数影响机器人位置准确度的问题,提出一种融合多坐标系的误差模型实现工业机器人运动学标定。该模型首先使用D-H模型建立机器人坐标系模型;然后,引入6参数模型描述坐标系间的齐次变换矩阵,建立融合多坐标系的误差模型;最后,使用最小二乘法进行参数辨识,将辨识得到的参数补偿到机器人结构参数中。对埃夫特ER6-C10机器人进行标定与补偿实验,并与MD-H误差模型辨识补偿后的效果进行对比。实验结果表明所提出的融合多坐标系的误差模型相比于MD-H模型将机器人平均位置误差降低了48.61%。

智慧制造环境下大数据驱动的机床组群互学习精度优化分析研究

提出了一种通过应用制造大数据来提高数控机床组群整体性能的新思路和实现方法,分析了以机床模型为中心的误差预测问题,介绍了机床组群实时加工数据的互学习精度参数优化方法,以及大数据驱动的机床加工精度优化路径,对数控机床互学习精度优化的关键技术进行分析。

基于虚拟材料层和孪生有限元模型的机床主轴固定结合部动力学建模

针对主轴系统固定结合部传统弹簧阻尼单元法等效建模精度较低的问题,采用虚拟材料层法建立主轴系统固定结合部的孪生物理模型,对模型进行有限元分析计算,以虚拟材料层相关参数(弹性模量、密度、泊松比)作为输入,计算机床主轴的固有频率,并以此数据样本训练深度神经网络,建立主轴系统的孪生有限元模型。采用粒子群优化算法,以虚拟材料层相关参数为优化变量,以孪生有限元模型计算的理论固有频率与对应试验值的相对误差最小为目标函数,优化确定虚拟材料层的相关参数。以VMC850E型立式加工中心主轴的刀柄-夹头-刀具系统两个固定结合部为实例进行了建模、试验、参数识别等分析,分析结果表明,该方法是可行的、有效的,建模精度达到了1%以内。

多轴数控机床伺服参数优化方法研究

数控机床在实际生产中,各轴伺服参数调整不好将影响机床的加工精度。为提高多轴联动中各轴伺服参数的匹配性,推导三轴数控机床加工轮廓误差的计算方法,分析三轴数控机床各轴进给系统伺服参数对轮廓误差的影响,提出2个进给轴之间伺服参数匹配方法。以人字齿的加工为例,对比了参数优化前后的实际加工轨迹,参数优化后人字齿的轮廓误差由优化前的300μm减小到100μm,各轴伺服参数匹配能够有效提高数控机床的加工精度。