Thermal error compensation method for machine center

High-speed machining (HSM) technology has become the most important application in metal cutting industries. However, overcome the positioning error is one of a great concern. The position error happens due to poor machine structure design and thermal expansion comes from cutting, especially when HSM is applied. In this paper, a new technique is developed to compensate for these errors. The thermal images are used to confirm dispersion of all the affect positions. PT-100 thermo-measuring sensors are applied to detect the thermal expansion. And a mathematical model is built by multi-variable regression analysis, which is based on the sensed temperature variation and the thermal expansion. Finally, these errors are reduced significantly by sending a feedback to the microprocessor. Meanwhile, the thermal deformation can be compensated by the mathematical model, under the condition when the machine is equipped with linear encoder. Moreover, based on the simulation, it is possible to reduce the number of sensors from ten to six, which save the memory capacity and great benefit for calculating and speeding the process of algorithm. The model improves the accuracy of machining which meets the precision requirement of HSM technology. As the result of various machining tests, the axial positioning error can be reduced from 20 μm to be 3 μm, which is a significantly improvement than existing methods.     

Thermal growth measurement and compensation for integrated spindles

The errors which affect the processing tolerance of a machine tool are due to the built-in volumetric errors in the machine tool structure and also the thermal displacement of the machine tools during its cutting. In this paper, a dual-displacement meter compensation system is developed. The new model has a better tolerance control than the single-displacement compensation meter method; also, it has a great potential for saving a machine’s warm-up time as well as enhancing productivity. A dual-displacement meter is designed to detect the variation of spindle thermal growth and a differential amplifier is applied which ensure a precise output signal tolerance of spindle thermal growth. The unstable signal which is an effect of flatness tolerance of spindle surface is then omitted. Finally, the spindle thermal growth compensations are successfully reduced. It meets the requirement of high-speed machining and high-precision machining application.     

Automated measurement and compensation of thermally induced error maps in machine tools

In this paper, a direct method of machine tool calibration is adopted to model and predict thermally induced errors in machine tools. This method uses a laser ball bar (LBB) as the calibration instrument and is implemented on a two-axis computerized numerical control turning center (CNC). Rather than individually measuring the parametric errors to build the error model of the machine, the total positioning errors at the cutting tool and spindle thermal drifts are rapidly measured using the LBB within the same experimental setup. Unlike conventional approaches, the spindle thermal drifts are derived from the true spindle position and orientation measured by the LBB. A neural network is used to build a machine model in an incremental fashion by correlating the measured errors with temperature gradients of the various heat sources during a regular thermal duty cycle. The machine model developed by the neural network is further tested using random thermal duty cycles. The performance of the system is also evaluated through cutting tests under various thermal conditions. A substantial improvement in the overall accuracy was obtained.     

Application of ACO-BPN to thermal error modeling of NC machine tool

Thermal errors are the major contributor to the dimensional errors of a workpiece in precision machining. Error compensation technique is a cost-effective way to reduce thermal errors. Accurate modeling of errors is a prerequisite of error compensation. In this paper, four key temperature points of a NC machine tool were obtained based on clustering method. A thermal error model based on the four key temperature points was proposed by using ant colony algorithm-based back propagation neural network (ACO-BPN). The ACO-BPN method improves the prediction accuracy of thermal deformation in the NC machine tool. A thermal error compensation system was developed based on the proposed model, and which has been applied to the NC machine tool in daily production. The results show that the thermal drift in workpiece diameter has been reduced from 33 to 8 μm from its center of tolerance.     

基于灰色系统理论的GM2000A数控机床热误差的智能补偿方式及应用

众所周知对于超精密机床而言,热误差是影响数控机床加工精度的重要因素之一,可达机床加工精度总误差的70%。因此减少热误差对数控机床的影响至关重要。要提高加工精度,减少热误差,就必须对其进行有效的补偿。以GM2000A龙门加工中心为对象介绍了热误差的测量方法,采用灰色系统理论中的灰色关联分析法建立测温点和热误差之间的相关程度达到优化测温点的目的,使输入数据更趋于合理。最后用BP神经网络建立温升和机床热误差之间的数学模型,MATLAB仿真实验结果表明了补偿效果的可行性。     

双转台五轴机床空间误差补偿技术研究

几何误差、热误差和切削力误差占到了机床总误差的75%,对这3项误差进行控制是提高机床加工精度的关键所在。以双转台五轴机床的空间误差作为研究对象,通过对加工位置、主要热源及电动机电流等相关因素进行分析,确定空间误差建模所需的位移变量、温度变量和切削力变量。以现有的多种误差建模方法为基础,通过对信息融合技术进行研究,提出一种机床空间误差的多模型融合预测方法,建立综合反映几何误差、热误差和切削力误差的最优空间误差模型。最后以DSP为核心,设计空间误差补偿器,实施空间误差补偿,验证补偿效果。结果显示,建立的模型预测精度较高,残差小于2μm,而实施空间误差补偿后,加工零件的轮廓误差也由15μm降到了5μm,补偿效果明显。     

基于有限元分析方法的高速电主轴温度场仿真

高速切削加工是先进制造技术的主要发展方向之一,高速电主轴作为高速加工机床的核心部件,由于其主电动机的散热条件较差,轴承温升比较高,由此引起的热变形会降低机床的加工精度。本文对高速电主轴的温度场进行了研究,建立了电主轴的有限元仿真系统。在对整个温度场的研究中,把内部空间域离散化为有限单元,对每个单元求解,可得出有限个热传导方程,对这些温度场求解得到了所需的温度场分布图。最终实现了对电主轴温度场的预测,并据此提出了改善其热态特性的措施。     

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.     

PRECISION CUTTING OF MOLDING DIE USING SQUARE END MILL

The precision cutting of a molding die is realized using a square end mill on a 5-axis control machine. In this study, first the tool setting errors are analyzed and the compensation method of the errors is proposed. The effectiveness of compensation in precision cutting is confirmed. Next, the form accuracy of the spiral tool pass is compared with contour one in precision cutting of a spherical surface. Finally, the molding die with spherical surface is manufactured using a square end mill made out of single-crystal diamond based on the results of the compensation of the errors and the comparison of the two tool passes, and the form accuracy and surface roughness of the molding die are measured.     

Temperature measurement and machining damage in slotting of multidirectional CFRP laminate

Compared to metallic materials, carbon fiber-reinforced plastics (CFRPs) have lower thermal conductivity and minor thermal expansion coefficient. Despite this, their machining can generate accuracy errors if the cutting temperature is not controlled. In this paper, an experimental study of slotting of multidirectional CFRP laminate (G803/914) with three micrograin carbide burr tools with different geometries is considered in order to investigate tool-workpiece contact point temperature, chip temperature, machined surface damage, subsurface defects and tool degradation. The experiment is made on a computer numerical control (CNC) machine with cutting speed ranging from 80 to 200 m/min and feed per tooth from 0.008 to 0.060 mm/rev/tooth. The data were analyzed in order to establish empirical models showing the dependence of cutting temperature on tool geometry and cutting conditions. Based on the results, it is concluded that cutting speed is the factor influencing cutting temperature the most, the heat generated during slotting is removed mainly by chips and the chip temperature is greater than the tool-workpiece contact temperature of about 18.5°C on average for the three burr tools.