Axes Of Five-axis Machine Tool Research Articles

Calibration of link errors in rotary axes of five-axis machine tools using a six-dimensional motion measuring device

In this study, the position-independent geometric errors (PIGEs) of five-axis machine tools are identified and calibrated using a Stewart–Gough platform (SGP) based Motion Measuring Device (MMD). As the MMD of micrometer-level accuracy is cable of six-dimensional pose measurements, a closed kinematic chain is established by installing the upper and lower plate of the MMD to the spindle and rotary worktable of the machine tool, respectively. Particularly, the sensor-mounting misalignments, which are inevitable but mostly ignored in the previous PIGE identification methods, are formulated and identified together with the PIGEs. Thus, the sensor-mounting misalignments will not affect the accuracy of PIGE calibration. The proposed method is verified by simulation and experimental results. The synchronous motion test (SMT) demonstrates that the five-axis machine tool owns a high accuracy of 5 micrometers in the tested motion range after PIGE calibration.

A new method to identify the position-independent geometric errors in the rotary axes of five-axis machine tools

Position-independent geometric errors (PIGEs), caused by assembly imperfection, affect the machine tool's accuracy. Moreover, the rotary axes of five-axis machine tools introduce more PIGEs during parts machining, hence, the need to identify them to improve the accuracy. However, the identification of rotary axes centerlines and the use of extension bars, using double ball bar (DBB), introduce additional setup errors and uncertainties during error measurements and sometimes make the process tedious. This work proposes a new method to identify the eight (8) PIGEs in the rotary axes of a five-axis machine tool with a tilting table. The homogeneous transformation matrix (HTM) was used to construct the relative motion matrix to the established coordinate systems and then deduced the error model. Three different DBB installation setups were employed for the identification of the PIGEs for both rotary axes using the planar test, the recorded DBB length data was substituted into the model to obtain the PIGEs. The results show that the proposed PIGEs identification method is accurate and can improve the accuracy of the five-axis machine tool effectively, and this method has some advantages over some existing methods of identification in terms of simplicity which shows a good improvement in the manufacturing industry.

Geometric error identification of five-axis machine tools using dual quaternion

A universal identification method for position independent geometric errors (PIGEs) of dual rotary axes of five-axis machine tools with arbitrary rotary axis position structures is proposed based on the unit dual quaternion (UDQ). The PIGEs of translational/rotary axes are redefined based on UDQ transformation, which effectively reduces the transformation parameters and avoids the unitization process of UDQ compared with the existing UDQ kinematics model. Based on the redefined PIGEs, a kinematic error model of a five-axis machine tool is established for error identification. Taking the cradle-type five-axis machine too with non-intersecting rotary axes as the research objective, a novel method for identifying PIGEs through the synchronous motion of dual rotary axes using a double ball bar (DBB) is proposed. Compared with BK1 and BK2 in ISO10791-6 and other existing methods, the advantage of the proposed method is that it can greatly reduce the complexity of the experiment and the operation steps by directly constructing the relative kinematic relationship between the tool and the workpiece based on the error model. Only one installation and one measurement trajectory are needed to simultaneously identify the eight PIGEs of the dual rotary axes. In addition, a trajectory equalization algorithm is proposed to effectively solve the asynchronous problem of motion and data sampling in DBB trajectory operation. By combining the simplified error model with the sampling data of DBB, the pseudo-inverse matrix is used for decoupling. The effectiveness of the proposed method is verified by DBB compensation comparison experiment. The proposed error identification method can be applied to other types of five-axis machine tools with a few changes in the configural parameters, which is ideal for periodic checks and calibration to ensure the machining accuracy.

Highly efficient and accurate calibration method for the position-dependent geometric errors of the rotary axes of a five-axis machine tool

This paper proposes a calibration method for continuous measurements with a double ball bar (DBB) used to identify the position-dependent geometric errors (PDGEs) of the rotary axes of five-axis machine tools. The different DBB installation modes for the rotary axes of the spindle and workbench are established, and the same initial DBB installation position is used for multiple tests. This approach minimizes the number of required DBB installations, which increases the measurement efficiency of the PDGEs of the rotary axes and reduces installation errors. PDGEs identification based on the adaptive least absolute shrinkage and selection operator (LASSO) method is proposed. By assigning coefficients to the PDGEs polynomial, the ill-conditioned problem of the identification process can be effectively avoided, thereby improving the identification accuracy. The measurement and identification methods proposed in this paper are verified by experiments on a five-axis machine tool. After compensation, the PDGEs are obviously reduced and the accuracy indexes of the circular trajectory tests performed under multiaxis synchronous control are obviously improved.

Self-calibration of rotary axis and linear axes error motions by an automated on-machine probing test cycle

Efficient, precise and automated in-process calibration schemes are essential to improve the accuracy and productivity of five-axis machine tools. This paper presents a new calibration approach, which combines an on-machine measurement cycle and self-calibration techniques, to evaluate the position errors and the error motions of a rotary axis using a touch trigger probe and an uncalibrated cylindrical artefact. This significantly reduces the downtime of machine tools required for the calibration process. In contrast to many common calibration strategies for rotary axes of five-axis machine tools, the presented self-calibration concept does not neglect the positioning errors of the linear axes when identifying the position errors and the error motions of the rotary axis. The self-calibration procedure is able to separate the positioning errors of the linear axes in radial direction, and the radial error motions and the position errors of a rotary axis, as well as the errors related to the uncalibrated artefact. This error separation is realized by a test cycle consisting of four tests in which the measurements are conducted by particular axis movements. Furthermore, an uncertainty analysis of the self-calibration concept is conducted to visualize the uncertainty propagation within the mathematical model. The self-calibration procedure is analyzed by an experimental evaluation, which includes a comparison between the results of the self-calibration approach and an R-Test. This comparison shows that the results of both measurement procedures are consistent.

Identification and compensation of position-dependent geometric errors of rotary axes on five-axis machine tools by using a touch-trigger probe and three spheres

For the machining accuracy of five-axis machine tools, it must be emphasized that not only the PIGEs but also the PDGEs of rotary axes influence the machining accuracy. However, until now there is no any commercial measurement system available for identifying the PDGEs in the rotary axes of five-axis machine tools. As a result, this study proposes a robust, efficient, and automatic measurement method to identify and compensate the position-dependent geometric errors (PDGEs) of rotary axes on five-axis machine tools. The proposed measurement method has established an on-machine measurement for the PDGEs of rotary axes by using a touch-trigger probe and three spheres installed on the spindle as well as the tilting rotary table, respectively. For each rotary axis, only a single measuring pattern is implemented to measure the PDGEs with a single setup, which delineates the advantages of efficient and automated identifying procedures in each periodical measurement. By implementing the proposed measurement method, 12 PDGEs can be numerically identified based on the measurement algorithm, which is built through a kinematic error model as well as a least square method. Finally, the proposed measurement method is experimentally conducted on a commercial five-axis machine tool. Moreover, after consequently performing the proposed measurement method, the PDGEs of the rotary axes were quantitatively compensated by the commercial controller to validate its feasibility. The experimental results have clearly delineated that the linear errors and angular errors are reduced from at most 37.81 μm and 10.23 mdeg to 0.9 μm and 0.26 mdeg, respectively. Consequently, the experimental results have demonstrated that the proposed measurement method is efficient and precise.

Position-independent geometric error identification and global sensitivity analysis for the rotary axes of five-axis machine tools

Position-independent geometric errors (PIGEs) are the fundamental errors of a five-axis machine tool. In this paper, to identify ten PIGEs peculiar to the rotary axes of five-axis machine tools with a tilting head, the mathematic model of the ten PIGEs is deduced and four measuring patterns are proposed. The measuring patterns and identifying method are validated on a five-axis machine tool with a tilting head, and the ten PIGEs of the machine tool are obtained. The sensitivities of the four adjustable PIGEs of the machine tool in different measuring patterns are analyzed by the Morris global sensitivity analysis method and the modifying method, and the procedure of the four adjustable PIGEs of the machine tool is given accordingly. Experimental results show that after and before modifying the four adjustable PIGEs, the average compensate rate reached 52.7%. It is proved that the proposed measuring, identifying, analyzing and modifying method are effective for error measurement and precision improvement of the five-axis machine tool.

A geometric error identification method for the swiveling axes of five-axis machine tools by static R-test

This paper proposes a new method to identify the 12 geometric error components of the swiveling axes of five-axis machine tools by static R-test. First, the geometric error modeling of a five-axis machine tool including the error sources of the C-A swiveling head is briefly introduced based on the MBS method. With the assistance of an auxiliary fixture, the measuring strategy of the swiveling axes that consists of six inspection modes by static R-test is proposed. Then, a geometric error identification algorithm for the C- and A-axis is respectively proposed based on the least square method. Numerical simulation is conducted and the results show that the accuracy of the identification algorithm can reach 89 %. An optimization method for the auxiliary fixture is proposed by minimizing the condition number of the identification matrixes to further improve the identification accuracy. Finally, numerical simulation shows that the identification accuracy can be increased to 97 % after optimization. The theoretical analysis and numerical simulation results indicate that the proposed swiveling axes geometric error identification method is both efficient and effective.

Accuracy evaluation of rotary axes of five-axis machine tools with a single setup of a double ball bar

A double ball bar (DBB) is used extensively to evaluate the geometric and dynamic performance of three-axis machine tools by means of the XY, YZ and XZ planar circular tests. However, research using a DBB to test the rotary axes of five-axis machine tools simply, quickly and effectively is scarce. In this paper, a method having two steps to identify the imprecision of the rotary axes caused by the position-independent geometric errors (PIGEs) is presented for a tilting rotary type five-axis machine tool using a DBB. The first step is designed to evaluate two rotary axes with one setup. Its advantage of fast diagnosis effectively reduces the machine down time, and thus can be employed as a quick testing approach of the machine tool. However, if some of the diagnosed errors fall outside their tolerances, a more accurate but slower check needs to be carried out due to the limitation of the first step. The second step aims to test the two rotary axes separately, each in two sub-steps. By means of varying the position of the pivot, the A- and C-axes can be tested individually. Both steps are performed with only one axis moving, thus simplifying the error analysis. Implementation of the proposed methods was carried out on a Hermle C600U five-axis machine tool. To show the validity of the method, the identified PIGEs are compensated for in each step, which suggests that the first step can be used as a fast and preliminary indication of a five-axis machine tool’s performance, whilst the second can be carried out if a more thorough evaluation is needed.

五轴机床旋转轴误差的在机测量与模糊径向基神经网络建模

五轴机床旋转轴误差的在机测量与模糊径向基神经网络建模

Compensation of position-independent and position-dependent geometric errors in the rotary axes of five-axis machine tools with a tilting rotary table

We describe a method to separate, measure, and compensate for position-independent and position-dependent geometric errors in the rotary axes of a five-axis machine tool with a tilting rotary table using double ball-bar measurements. The measurement paths require control of a single rotary axis, and they are not affected by the accuracy of the linear axes. The positions of the balls of the double ball-bar are modeled as the nominal positions, with geometric errors considered via a kinematic analysis to represent the measurement configuration. The method is applied to measure both position-independent and position-dependent geometric errors, and the results are verified via measurements with compensation for the geometric errors. Furthermore, the possible range of the measured geometric errors is determined by analyzing the contributors.

Using a double ball bar to identify position-independent geometric errors on the rotary axes of five-axis machine tools

A measuring method using a double ball bar (DBB) is proposed for identifying the eight position-independent geometric errors (PIGE) on the rotary axes of five-axis machine tools. Three measuring patterns are used, in which the translational axes are kept stationary and only two rotary axes move to obtain a circular trajectory. In this way, the effects of translational axes are totally excluded, and the measurement accuracy is improved. Motion equations, describing how the A-axis and C-axis move simultaneously to realize a circular trajectory, are presented. The influence of each deviation on the measurement patterns is simulated, and analytical solutions for the eight PIGEs are demonstrated. Finally, the measuring method is verified in a five-axis CNC machine tool. Experimental results confirm that the method provides precision results for the eight PIGEs.

Double Ballbar Measurement for Identifying Kinematic Errors of Rotary Axes on Five-Axis Machine Tools

This paper proposes a novel measuring method which uses double ballbar (DBB) to inspect the kinematic errors of the rotary axes of five-axis machine tool. In this study, kinematic error mathematical model is firstly established based on the analysis of the rotary axes errors which originated from five-axis machine tools. In the simulation, working conditions considering different error origins are simulated to find the relationship between the DBB measuring patterns and the kinematic errors. In the measuring experiment, the machine rotary axes move simultaneously along a specified circular path while all the linear axes are kept stationary. The original DBB measuring data are processed to draw the measuring patterns in the polar plots which can be employed to observe and identify the kinematic errors. Rotary error compensation is implemented based on the function of external machine origin shift. Both the simulation and the experiment results show the convenience and effectiveness of the proposed measuring method as well as its operability as a calibration method of five-axis machine tools.

Geometric Error Identification and Compensation for Rotation Axes of Five-Axis Machine Tools

In NC machining, the precision of the final parts is affected by many factors, including geometric deviation of machine tool components and structures, deformation of process system caused by cutting force and cutting heat, servo delay, tool wear and so on. Among which geometric error of machine tool is one of the most important factors. This study focused on geometric error identification and compensation of rotation axes of five-axis machine tools. A new method was proposed to identify the 6 geometric error parameters of each rotation axes of five-axis machine tools based on a ball-bar system. Regarding the machine tool as a rigid multi-body system (MBS), a geometric error model was established based on homogeneous transfer matrix (HTM). Finally, the geometric errors were compensated by correcting NC codes by the prototype software system developed in this study. An experiment and an application were conducted and the results show that the proposed method is effective to improve the machining accuracy.