精密复杂零件数控加工在线检测与误差补偿技术研究

针对精密复杂零件数控加工离线检测误差大、效率低,在线检测尺寸、形状受限制等问题,建立了基于B样条曲面的确定性曲面回归模型,通过对回归模型残差空间独立性分析,将复杂零件的数控加工误差分解为系统误差和随机误差,通过修改数控代码,实现了精密复杂零件数控加工在线检测及误差补偿。为验证有效性,进行了大量试验,将试验结果与CMM检测结果对比,结果显示提出的在线检测及误差补偿方法行之有效,实现了精密复杂零件数控加工"加工-测量-补偿加工"的闭环制造。     

精密复杂零件数控加工在线检测误差补偿研究

精密复杂零件数控加工产生误差的影响因素较多,难以精确找出各影响因素与加工误差之间的对应关系。从精密复杂零件数控加工精度检测数据出发,建立了基于B样条的精密复杂零件回归模型。通过对回归模型残差空间独立性进行分析,将加工误差分解为系统误差与随机误差。根据分解出的系统误差大小,修改数控代码,进行补偿加工,有效提高了精密复杂零件的数控加工精度。将试验结果与三坐标测量机检测结果进行对比,结果显示在线检测误差补偿方法行之有效。     

复杂曲面零件加工精度原位检测系统的残余误差补偿

复杂曲面零件数控加工后直接进行原位加工精度检测和误差补偿,是实现精密产品闭环制造模式的有效途径。原位检测系统的误差来源于测量系统误差和机床运动系统误差,经相关的误差分离与误差补偿后,仍存在较大的残余误差,影响检测精度及其推广应用。针对原位检测系统的检测精度问题,开展检测系统残余误差的回归建模与补偿研究,在机床几何误差、测头半径误差以及预行程等基本误差补偿的基础上,建立基于偏最小二乘回归分析算法的误差回归模型,实现曲面零件测点法矢方向的检测数据二次补偿。在算法实现的基础上,列举复杂曲面零件进行数控加工与在线检测的试验研究。试验结果表明,二次误差补偿方法可以进一步提高原位检测系统的检测精度。     

基于经验模态分解方法的曲面加工误差补偿

采用误差补偿技术对曲面的加工误差进行补偿是提高该类零件加工精度的有效方法。针对加工误差进行经验模态分解,将加工误差分解为若干个固有模态函数(IMF)和一个res趋势项函数。根据系统误差的特征,趋势项函数中一定存在系统误差,利用自相关分析法和频谱图对固有模态函数分析是否存在周期性变化系统误差,最终分解出系统误差和随机误差。搭建了数控机床在线检测的实验平台,实现了曲面零件的系统误差补偿。通过一个曲面零件的加工实验表明,补偿加工后的曲面精度提高了86.0%。仿真算例和实验结果表明,基于经验模态分解方法的加工误差补偿能有效提高曲面零件的加工精度。     

基于AutoCAD的数控车床在线检测系统

介绍基于AutoCAD的数控车床在线工件自动检测系统的系统构架和功能。给出车床上测头的安装及标定方法,提出基本几何体和曲面零件检测路径规划和检测数控代码的生成方法,研究在线检测过程中零件热变形补偿及检测误差评定问题。运用AutoCAD的ObjectARX的二次开发平台,开发出数控车床在线检测系统。该系统具有代码自动生成、热变形误差补偿及检测报告生成等功能,可用于基本轴、孔类零件和曲面类零件的加工精度在线检测。     

数控加工误差主动补偿方法

为提高零件的加工精度,提出了基于公差的局部误差补偿法,并通过修正数控程序主动补偿加工误差.分析零件加工表面误差的特点,根据实际公差要求找出超出公差范围的变形关键区域,修正其切削深度以实现误差的局部补偿.得到刀位控制点修正的切深后,重新规划带有误差补偿值的刀具轨迹.结合实际加工精度确定走刀步距和行距,经过后置处理生成零件修正的数控代码.通过实例验证了上述方法的可行性.     

加工精度在线检测系统预行程误差预测与补偿

预行程误差的预测和补偿能够大大提高加工精度在线检测系统的测量精度.提出了一种基于BP神经网络的检测误差预测新方法,建立了一个基于BP神经网络的在线检测系统预行程误差预测模型,通过实验数据对该网络进行训练,并将训练好的神经网络应用到实际加工零件的误差预测和补偿.为了验证该方法的有效性,以一圆柱零件的圆度误差检测为例,对其加工精度的在线测量进行了预行程误差的预测与补偿,经与CMM检测结果的对比,说明了该方法的有效性.     

复杂曲面的数控加工误差分析

针对复杂曲面的多轴数控加工,应用数学知识建模,从理论上分析了平底铣刀刀具加工复杂曲面时的误差,得出了影响数控加工精度的主要因素并提出了误差补偿方法,为控制多轴数控加工的误差提供了理论依据与补偿算法,对高精度复杂曲面的数控加工具有借鉴意义。     

数控加工复杂曲面的误差分析和补偿

介绍了五轴数控机床加工复杂曲面的工作原理，重点分析了五轴数控加工时采用环形铣刀加工复杂曲面的误差模型，提出了误差补偿的具体方法。为提高复杂曲面数控加工精度具有指导意义。     

复杂曲面零件加工精度的原位检测误差补偿方法

为提高复杂曲面零件的数控机床原位检测精度,分析影响接触式检测系统精度的各项因素及其误差补偿方法。对检测系统的主要误差来源如机床几何误差、测头预行程误差和测头半径误差进行分析研究。在对数控机床的几何误差进行分析和建模的基础上,采用激光干涉仪进行三轴数控机床的单项误差测量和补偿;针对测头检测过程中存在的预行程误差,提出基于径向基函数(Radial basis function, RBF)的预行程误差预测方法,获得测头预行程误差分布图,并对检测系统进行实时预行程误差的补偿;提出改进的三角网格模型顶点法矢计算方法,有效进行三维测头的半径补偿。通过实例零件的加工精度原位检测试验及其与三坐标测量机CMM检验结果的比较,验证了原位检测方法的有效性。     

工件分特征下的五轴数控机床关键几何误差分析与补偿方法

提出了工件分特征下的五轴数控机床关键几何误差分析与补偿方法,将复杂工件进行特征分解,通过灵敏度分析辨识工件分特征下的关键几何误差并补偿,从而提高工件整体加工精度。以某一复杂工件为例,首先,将其分解为平面、斜面、圆柱和圆锥台四个典型特征;然后,基于灵敏度分析分别辨识出各典型特征对应的关键几何误差;最后,分特征地进行误差补偿。在AC双转台五轴数控机床上进行了实验验证,实验结果表明,辨识得到的关键几何误差灵敏度系数之和占比均大于90%,补偿后工件四个典型特征的加工精度提高了20%~30%。研究结果表明,所提方法能有效辨识不同工件分特征下的关键几何误差,从而提高复杂工件的加工精度。     

Prediction and compensation of machining geometric errors of five-axis machining centers with kinematic errors

Kinematic errors due to geometric inaccuracies in five-axis machining centers cause deviations in tool positions and orientation from commanded values, which consequently affect geometric accuracy of the machined surface. As is well known in the machine tool industry, machining of a cone frustum as specified in NAS979 standard is a widely accepted final performance test for five-axis machining centers. A critical issue with this machining test is, however, that the influence of the machine's error sources on the geometric accuracy of the machined cone frustum is not fully understood by machine tool builders and thus it is difficult to find causes of machining errors. To address this issue, this paper presents a simulator of machining geometric errors in five-axis machining by considering the effect of kinematic errors on the three-dimensional interference of the tool and the workpiece. Kinematic errors of a five-axis machining center with tilting rotary table type are first identified by a DBB method. Using an error model of the machining center with identified kinematic errors and considering location and geometry of the workpiece, machining geometric error with respect to the nominal geometry of the workpiece is predicted and evaluated. In an aim to improve geometric accuracy of the machined surface, an error compensation for tool position and orientation is also presented. Finally, as an example, the machining of a cone frustum by using a straight end mill, as described in the standard NAS979, is considered in case studies to experimentally verify the prediction and the compensation of machining geometric errors in five-axis machining.     

光学自由曲面快速刀具伺服车削误差的补偿

受各种误差因素以及周期性变化的切削力的影响,快速刀具伺服金刚石车削技术往往难以用一次车削获得满足光学性能要求的自由曲面。本文提出了一种利用线性差动传感器(LVDT)实现高精度接触式自由曲面在位测量的方法。该方法结合两自由度快速刀具伺服系统,实现了基于快速刀具伺服(FTS)的自由曲面车削加工的误差补偿。试验结果表明,该技术将自由曲面的加工精度提高了20%,表面粗糙度降低18.1%,解决了FTS系统与机床运动的同步问题,可补偿机床xyz三向运动误差,可用于自由曲面加工误差的修正。该方法还可用于不对称幅度较大的曲面或硬脆性材料的加工等,故促进了高精度光学自由曲面的推广应用。     

龙门式多轴联动机床的几何误差建模

设计一台集加工、检测于一体的小型龙门式多轴联动加工系统,以实现小型或微小型零件的铣、钻、磨削加工。机床除了从结构上提高精度外,也采取了误差补偿的措施,通过对机床进行几何误差建模,得到几何误差模型,以便进行补偿,提高精度。     

An integrated error compensation method based on on-machine measurement for thin web parts machining

Thin webs are widely used in the aerospace industry for the advantages of compact structure, light weight and high strength-to-weight ratio. Due to its low rigidity, serious machining error may occur, therefore, Finite Element method and mechanism analysis are usually utilized to modeling its deformation. However, they are very time-consuming and only suitable for elastic deformation error. In this study, an integrated error compensation method is proposed based on on-machine measurement (OMM) inspection and error compensation. The OMM inspection is firstly applied to measure the comprehensive machining errors. The Hampel filtering is then used to eliminate outliers, followed by the triangulation-based cubic interpolation as well as a machine learning algorithm which are used to establish the compensation model. At last, the real time compensation of high-density cutting points is realized by developing the compensation system based on External Machine Zero Point Shift (EMZPS) function of machine tool. Three sets of machining experiment of a typical thin web part are conducted to validate the feasibility and efficiency of the proposed method. Experiment results revealed that after compensation, the comprehensive machining errors were controlled under different machining conditions and 58.1%, 68.4% and 62.6% of the machining error ranges were decreased, respectively. This method demonstrates immense potential for further applications in efficiency and accuracy improvement of thin-walled surface parts.     

Frequency domain error analysis in turning

In spite of the large body of work on error analysis in turning, there are very few references that directly address the relationship between the original frequency content of the different dynamic errors of the machine tool and of the machining process and the resulting spatial frequency content of the machined surface. In this paper, the dynamic errors of a machine tool are classified into two categories: (a) kinematics-induced and (b) vibration-induced dynamic errors. Through a theoretical analysis, it will be shown that the spatial frequency content of the turned surface is not directly influenced by the original frequency factors of the machine dynamic error components, but by the aliased frequency factors which will be explained in this paper. On the basis of the establishment of the deterministic mathematical relationship between the frequency contents of the machine dynamic errors in the volumetric error model and the spatial frequency content of the turned surface in radial directions, a method for obtaining the frequency spectrum of the machined surface error in radial directions is given. In addition, a method to influence the number of spatial frequency components of the surface error in radial directions and to predict and control their magnitude is put forward. A case study of a flat surface turning is presented to highlight the effectiveness of the theoretical analysis and of the proposed methods. This study has potential applications in predicting and controlling the spatial content of machined surfaces, in selecting proper machining conditions, as well as in designing machine tools for applications in which strict spatial frequency requirements are placed on the workpiece surface.     

Prioritization analysis and compensation of geometric errors for ultra-precision lathe based on the random forest methodology

Geometric errors remarkably affect the dimensional accuracy of parts manufactured by ultra-precision machining. It is vital to consider the workpiece shape for the identification of crucial error types. This research investigates the prioritization analysis of geometric errors for arbitrary curved surfaces by using random forest. By utilizing multi-body system (MBS) theory, a volumetric error model is initially established to calculate tool position errors. An error dataset, which contains information of 21 geometric errors, workpiece shape, and dimensional errors, is then constructed by discretizing the workpiece surface along the tool path. The problem of identifying crucial geometric errors is translated into another problem of feature selection by applying random forest on the error dataset. Moreover, the influence extent of each geometric error on the dimensional accuracy of four typical curved surfaces is analyzed through numerical simulation, and crucial geometric errors are identified based on the proposed method. Then, an iterative method of error compensation is proposed to verify the reasonability of the determined crucial geometric errors by specifically compensating them. Finally, under compensated and uncompensated conditions, two sinusoidal grid surfaces are machined on an ultra-precision lathe to validate the prioritization analysis method. Findings show that the machining accuracy of the sinusoidal grid surface with crucial geometric error compensation is better than that without compensation.     

CNC加工动态基准视觉检测新工艺研究

由于CNC加工过程中工序间误差累积,严重影响数控加工精度。为此提出一种CCD视觉检测新工艺来实现加工动态基准的在线检测和误差补偿。研究动态基准的视觉特征提取方法,获取加工基准位置和误差;采用嵌入式控制技术,实现视觉图像的在线采集和处理;视诊测头像普通刀具一样通过标准锥柄安装在加工中心刀库中,通过CNC程序代码实现一体化控制功能。针对汽车关键件的验证,得出视诊测头检测精度达到0.03 mm,与基于触发式测头的CNC在线检测方法相比,检测效率提高近3倍,证明了该检测工艺在检测精度及效率上均能够满足生产线自动化检测需求。     

Neural network-based modelling and error compensation of thermally-induced spindle errors

This research is concerned with enhancing the accuracy of a machining centre by compensating for thermally induced spindle errors in real-time. A neural network model was developed for on-line thermal error monitoring. A PC-based error compensation scheme was also developed to upgrade a commercial CNC controller for real-time thermal error compensation without any hardware modifications to the machine. The spindle thermal errors of a vertical machining centre were reduced by 70% after compensation.