STUDY ON THE COMPENSATION TECHNIQUE OF POSITIONING ERRORS FOR NC MACHINE TOOLS

Through analysis of the basic transformation of a typical body,the error transformations of the position vector and the displacement vector are employed,a general model for positioning errors of NC machine tools by using kinematics of the multi body system is discussed.By means of 8031 single chip system,intelligent error compensation controller has been developed.The results of experiments on XH714 machining center show that the positioning accuracy is enhanced effectively by more than 50%.

Modeling Approach of Regression Orthogonal Experiment Design for Thermal Error Compensation of CNC Turning Center

The thermal induced errors can account for as much as 70% of the dimensional errors on a workpiece. Accurate modeling of errors is an essential part of error compensation. Base on analyzing the existing approaches of the thermal error modeling for machine tools, a new approach of regression orthogonal design is proposed, which combines the statistic theory with machine structures, surrounding condition, engineering judgements, and experience in modeling. A whole computation and analysis procedure is given. Therefore, the model got from this method are more robust and practical than those got from the present method that depends on the modeling data completely. At last more than 100 applications of CNC turning center with only one thermal error model are given. The cutting diameter variation reduces from more than 35 μm to about 12 μm with the orthogonal regression modeling and compensation of thermal error.

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.

Temperature Variable Optimization for Precision Machine Tool Thermal Error Compensation on Optimal Threshold

Machine tool thermal error is an important reason for poor machining accuracy. Thermal error compensation is a primary technology in accuracy control. To build thermal error model, temperature variables are needed to be divided into several groups on an appropriate threshold. Currently, group threshold value is mainly determined by researchers experience. Few studies focus on group threshold in temperature variable grouping. Since the threshold is important in error compensation, this paper arms to find out an optimal threshold to realize temperature variable optimization in thermal error modeling. Firstly, correlation coefficient is used to express membership grade of temperature variables, and the theory of fuzzy transitive closure is applied to obtain relational matrix of temperature variables. Concepts as compact degree and separable degree are introduced. Then evaluation model of temperature variable clustering is built. The optimal threshold and the best temperature variable clustering can be obtained by setting the maximum value of evaluation model as the objective. Finally, correlation coefficients between temperature variables and thermal error are calculated in order to find out optimum temperature variables for thermal error modeling. An experiment is conducted on a precise horizontal machining center. In experiment, three displacement sensors are used to measure spindle thermal error and twenty-nine temperature sensors are utilized to detect the machining center temperature. Experimental result shows that the new method of temperature variable optimization on optimal threshold successfully worked out a best threshold value interval and chose seven temperature variables from twenty-nine temperature measuring points. The model residual of z direction is within 3 μm. Obviously, the proposed new variable optimization method has simple computing process and good modeling accuracy, which is quite fit for thermal error compensation.

Thermal Error Compensation for Telescopic Spindle of CNC Machine Tool Based on SIEMENS 840D System

In this paper, eddy current sensors and thermocouple sensors were employed to measure the thermal field and thermal deformation of a spindle of a telescopic CNC boring-milling machine tool, respectively. A linear regression method was proposed to establish the thermal error model. Furthermore, two compensation methods were implemented based on the SIEMENS 840D system by using the feed shaft of z direction and telescopic spindle respectively. Experimental results showed that the thermal error could be reduced by 73.79% when using the second compensation method, and the thermal error could be eliminated by using the two compensation methods effectively.

IMPROVING ACCURACY OF CNC MACHINE TOOLS THROUGH COMPENSATION FOR THERMAL ERRORS

A method for improving accuracy of CNC machine tools through compensation for the thermal errors is studied. The thermal errors are obtained by 1 D ball array and characterized by an auto regressive model based on spindle rotation speed. By revising the workpiece NC machining program, the thermal errors can be compensated before machining. The experiments on a vertical machining center show that the effectiveness of compensation is good.

Thermal Error Modeling Method with the Jamming of Temperature-Sensitive Points'Volatility on CNC Machine Tools

Aiming at the deficiency of the robustness of thermal error compensation models of CNC machine tools, the mechanism of improving the models＇ robustness is studied by regarding the Leaderway-V450 machining center as the object. Through the analysis of actual spindle air cutting experimental data on Leaderway-V450 machine, it is found that the temperature-sensitive points used for modeling is volatility, and this volatility directly leads to large changes on the collinear degree among modeling independent variables. Thus, the forecasting accuracy of multivariate regression model is severely affected, and the forecasting robustness becomes poor too. To overcome this effect, a modeling method of establishing thermal error models by using single temperature variable under the jamming of temperature-sensitive points＇ volatility is put forward. According to the actual data of thermal error measured in different seasons, it is proved that the single temperature variable model can reduce the loss of fore- casting accuracy resulted from the volatility of tempera- ture-sensitive points, especially for the prediction of cross quarter data, the improvement of forecasting accuracy is about 5 μm or more. The purpose that improving the robustness of the thermal error models is realized, which can provide a reference for selecting the modelingindependent variable in the application of thermal error compensation of CNC machine tools.

STUDY ON THE FEEDFORWARD COMPENSATION OF THE MOTIONERRORS OF NC MACHINE TOOLS

A feedforward compensation naethod of the motion errors of NC machine tools imple- mented with software is proposed , with which the motion errors can be compensated whithout changing the original computer control systems of the NC machine tools. The experimental results show that the circular interpolation profile machining errors decrease by a factor of 2/3 after com- pensated.

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.

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.

Error compensation for precision machine tools

As one of the ways to improve the machining accuracy of machine tools, error compensation is reviewed from different view points, and the main barriers to further improvement of efficiency of error compensation are analyzed in detail and the vista of the error compensation in precision and ultra precision machines is discussed.

Key point selection in large-scale FBG temperature sensors for thermal error modeling of heavy-duty CNC machine tools

Thermal error is one of the main factors that influence the machining accuracy of computer numerical control(CNC)machine tools.It is usually reduced by thermal error compensation.Temperature field monitoring and key temperature measurement point(TMP)selection are the bases of thermal error modeling and compensation for CNC machine tools.Compared with small-and medium-sized CNC machine tools,heavy-duty CNC machine tools require the use of more temperature sensors to measure their temperature comprehensively because of their larger size and more complex heat sources.However,the presence of many TMPs counteracts the movement of CNC machine tools due to sensor cables,and too many temperature variables may adversely influence thermal error modeling.Novel temperature sensors based on fiber Bragg grating(FBG)are developed in this study.A total of 128 FBG temperature sensors that are connected in series through a thin optical fiber are mounted on a heavy-duty CNC machine tool to monitor its temperature field.Key TMPs are selected using these large-scale FBG temperature sensors by using the density-based spatial clustering of applications with noise algorithm to reduce the calculation workload and avoid problems in the coupling of TMPs for thermal error modeling.Back propagation neural network thermal error prediction models are established to verify the performance of the proposed TMP selection method.Results show that the number of TMPs is reduced from 128 to 5,and the developed model demonstrates good prediction effects and strong robustness under different working conditions of the heavy-duty CNC machine tool.

Spindle Thermal Error Optimization Modeling of a Five-axis Machine Tool

Aiming at the problem of low machining accu- racy and uncontrollable thermal errors of NC machine tools, spindle thermal error measurement, modeling and compensation of a two turntable five-axis machine tool are researched. Measurement experiment of heat sources and thermal errors are carried out, and GRA（grey relational analysis） method is introduced into the selection of tem- perature variables used for thermal error modeling. In order to analyze the influence of different heat sources on spindle thermal errors, an ANN （artificial neural network） model is presented, and ABC（artificial bee colony） algorithm is introduced to train the link weights of ANN, a new ABC- NN（Artificial bee colony-based neural network） modeling method is proposed and used in the prediction of spindle thermal errors. In order to test the prediction performance of ABC-NN model, an experiment system is developed, the prediction results of LSR （least squares regression）, ANN and ABC-NN are compared with the measurement results of spindle thermal errors. Experiment results show that the prediction accuracy of ABC-NN model is higher than LSR and ANN, and the residual error is smaller than 3 pm, the new modeling method is feasible. The proposed research provides instruction to compensate thermal errors and improve machining accuracy of NC machine tools.

Structural scheme and theory behind feedback compensation of new parallel machine tools

Analyses the errors of new parallel machine tools and presents a structural scheme for feedback compensation of machine tools to eliminate these errors, the theory behind and the relation between direction consine of normal vector of the workpiece surface and the rotation angles α,β,γ of the cutter head.

Numerical Investigation of Thermal Behavior of CNC Machine Tool and Its Effects on Dimensional Accuracy of Machined Parts

The dimensional accuracy of machined parts is strongly influenced by the thermal behavior of machine tools (MT). Minimizing this influence represents a key objective for any modern manufacturing industry. Thermally induced positioning error compensation remains the most effective and practical method in this context. However, the efficiency of the compensation process depends on the quality of the model used to predict the thermal errors. The model should consistently reflect the relationships between temperature distribution in the MT structure and thermally induced positioning errors. A judicious choice of the number and location of temperature sensitive points to represent heat distribution is a key factor for robust thermal error modeling. Therefore, in this paper, the temperature sensitive points are selected following a structured thermomechanical analysis carried out to evaluate the effects of various temperature gradients on MT structure deformation intensity. The MT thermal behavior is first modeled using finite element method and validated by various experimentally measured temperature fields using temperature sensors and thermal imaging. MT Thermal behavior validation shows a maximum error of less than 10% when comparing the numerical estimations with the experimental results even under changing operation conditions. The numerical model is used through several series of simulations carried out using varied working condition to explore possible relationships between temperature distribution and thermal deformation characteristics to select the most appropriate temperature sensitive points that will be considered for building an empirical prediction model for thermal errors as function of MT thermal state. Validation tests achieved using an artificial neural network based simplified model confirmed the efficiency of the proposed temperature sensitive points allowing the prediction of the thermally induced errors with an accuracy greater than 90%.

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.

An Universal Modeling Method for Enhancing the Volumetric Accuracy of CNC Machine Tools

Volumetric error modeling method is an important te ch nique for enhancement the accuracy of CNC machine tools by error compensation. I n the research field, the main question is how to find an universal kinematics m odeling method for different kinds of NC machine tools. Multi-body system theor y is always used to solve the dynamics problem of complex physical system. But t ill now, the error factors that always exist in practice system is still not con sidered. In this paper, the accuracy kinematics of MBS (multi-body system) are developed by adding the movement error items and the positioning error items for every couple of adjacent bodies. After make an analysis for different kinds of NC machine tools we can find that NC machine tools can be looked as a kind of sp ecial MBS. It’s main construction only contains two movement branch. the one is from base part to workpiece and the other is from base part to cutter. So an u niversal volumetric error modeling method and the error analysis method for NC m achine tools can be built in this paper based on MBS theory. The essential condi tion for precision machining is derived through mathematics equations and the co ncept of ICCP (inverse changed cutter path ) and ICNI (inverse changed NC instru ction ) are presented in this paper. The numerical solution methods for ICCP and ICNI are also given in this paper which can be directly used to enhance the mac hining accuracy of NC machine tools. In order to verifying the above works, the double frequency laser interface detecting instrument of RENISHAW is used to mea sure the error parameters of the MAKINO 3-axis NC machine tools and the softwar es are developed using C++ developing language to simulate the cutte r trail under different kind conditions in the computer. Latterly the standard w ork parts are selected to be machined on the MAKINO 3-axis NC machine tools bef ore and after use the above mentioned error compensation method respectively. Th e simulation and experiment results show that the volumetric error modeling meth od is effective and the machining accuracy of CNC machine tools can be improved more than 60% after using the compensation method presented in this paper.

CNC机床丝杠热误差实时补偿设计及自动补偿试验

为了降低数控机床丝杠传动系统因热误差引起的定位误差,完成机床工作台各运行阶段的实时补偿。用非接触模式为丝杠非电机连接端安装位移检测器,以电涡流传感器时间监测丝杠端面位置数据,获得丝杠产生的总热误差,通过热补偿得到每段丝杠的热误差程度,确定每段坐标系原点发生的偏移,完成自主补偿机床丝杠热误差的效果。研究结果表明:采用分段补偿方法可以获得比其他热误差补偿模型更优的丝杠全段补偿性能。分别检测丝杠各段发生的热误差再对其实施补偿,可以根据丝杠各部位热误差程度实施补偿。

STUDYING ON THE PARAMETER IDENTIFIOATION OF GEOMETRIC ERRORS FOR NO MAOHINE TOOLS

An improved 22--line method of parameters identification for geometric errors of NC machine tools is discussed. All models are verified by a series of experiments on XH714 machining center. This method is available to identify geometric error parameters for three-coordinate equipment such as NC machining center and CMM.