Face- and Body-Diagonal Length Tests using a Double Ball-Bar for Squareness Errors of Machine Tools

Error compensation is one of effective and economical means to improve the machining accuracy of machine tools. The measurement accuracy of kinematic errors has great impact on the accuracy of machine tool error modeling. Some measurement errors are inevitably generated due to the distortion of the slide table and the limit of local measuring stroke. To solve these problems, an improved machine tool volumetric error compensation method is proposed in this paper, based on linear and squareness error correction method. The linear errors, including position errors and straightness errors, are corrected by considering the distance effect between optical mirror groups and the surface of worktable. The squareness errors are corrected through modifying local squareness errors measured with double ball bar to global squareness errors, with the aid of straightness errors measured with multi-laser calibrator. Then volumetric errors are obtained based on multi-body system theory, and volumetric diagonal errors are measured with laser interferometer. It is illustrated that the bidirectional systematic deviation of positioning of four volumetric diagonals reduced about 81.3%, 35.2%, 29.2%, and 4.5% respectively by using this improved machine tool volumetric error compensation method, and it is of obvious advantages in contrast with traditional compensation method with direct measurement data. The improved error compensation method proposed in this paper has universal applicability and has great significance on machine tool accuracy improvement.

Modeling and analysis of nonlinear guideway for double-ball bar (DBB) measurement and diagnosis

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.

This paper describes a newly developed forward kinematic calibration method for parallel mechanisms, which identifies the kinematic parameters using the positioning data measured by a Double Ball Bar (DBB) system. This method enables precise calibration with easy measurements, which improves the static accuracy reduced by kinematic parameter errors. This paper also describes a new gravity compensation method, in which the kinematic parameters are updated gradually according to the travelling plate position. This provides real-time motion control with compensation. These methods are applied to the parallel-mechanism-based milling machine, named HexaM, and their validity is verified by simulation and experiment.

Laser non-contact precision measuring method of CNC machine tools under the high feed rate condition was put forward. The method combines the laser interferometer with the measurement principle of the double ball bar (DBB), and can measure the machine tool precision under the high feed rate condition. Two laser interferometers used as measuring the displacements and feed rate data along circular interpolation motion individually measured three group data in the XY, YZ and XZ work planes, and the space errors of the CNC can be acquired through solving the special mathematic model based on the measurement principle of DBB.

During five-axis CNC machining, the dynamic tracking error caused by imperfect servo dynamic performance is becoming the major factor affecting the accuracy during high-speed and high-precision manufacturing. The double ballbar (DBB) test is one of the commonly used dynamic performance tests, but existing DBB test methods do not have satisfactory test capability for the requirement of complex freeform surface machining. In this paper, on the basis of summarized of dynamic tracking error’s mechanism and characteristics, an improved dynamic performance test based on DBB, which is named the circle-8 test, is proposed. In this test, a provenly efficient RTCP test trajectory is used to rebuild the DBB test process, which includes complex movements of all the five motion axes. To exhibit the improvement of the circle-8 test, this test and the BK3 test of ISO standard, which is considered as a comparison, are conducted in a five-axis machine tool with a tilting rotary table. According to the simulation and experiment results, for common dynamic inaccuracy situations, the circle-8 test always has better sensitivity of dynamic performance test than BK3 test. The above-improved dynamic performance test can be applied to provide effective data for the research of modeling and error reduction of five-axis machine tools.

A three-point method based on sequential multilateration is applied to measuring the geometric error components (GECs) of three-axis machine tools (MTs). To meet the accuracy requirement of geometric error mapping, a sequential multilateration scheme is developed for high-accuracy point measurement by introducing four additional targets into the measuring system, and the uncertainty of point measurement is verified by simulation. Three independent targets fixed on the MT’s spindle assembly move along with each axis step by step and their coordinates at each step can be determined by the distance data acquired by laser tracker at all steps based on sequential multilateration. Then the volumetric errors of the three target points can be obtained by comparing the actual coordinates and the corresponding desired coordinates, and nine equations can be established by substituting volumetric errors into the error model of linear axis, so that the six GECs of each axis can be obtained by solving these equations. The three squareness errors can be determined by computing the angles between the average lines of the three axes which are achieved by linear curve fitting. Experiments are conducted to measure these 21 GECs, and the volumetric errors in the three-axis MT’s workspace, which are determined by these measured GECs based on the error model of three-axis MT, are compensated. Finally, the positioning errors of the MT with compensation and without compensation are evaluated by laser interferometer, respectively, the experimental results of which demonstrate that the positioning errors are significantly reduced by the error compensation.

Identification and compensation of position independent geometric errors of dual rotary axes for hybrid-type five-axis machine tool based on unit dual quaternions

Identification of position-dependent geometric errors with non-integer exponents for Linear axis using double ball bar

The contouring accuracy of a multi-axis machine has a critical effect on the quality of many advanced technology products. One of the best approaches to assessing the contouring performance of machine tools is through double ball bar measurement. During circular interpolation motion, the machine traverses, with two axes at a time, a circular trajectory, with each axis subject to sinusoidal changes in acceleration, velocity, and position. The motion error is measured by detecting the relative distance between a point on the spindle nose and another point on the machine table and plotting this distance in polar coordinates. The present paper derives mathematical models and diagnosis procedures for first and second-order motion error resulting from the active degrees of freedom of a multi-axis machine. The theoretical results are verified by both computer simulation and double ball bar testing experiments.

Development of a measuring method for several types of programmed tool paths for NC machine tools using a laser displacement interferometer and a rotary encoder

Geometric errors are one of the primary potential sources of error in a five-axis machine tool. There are two types of geometric errors: position-dependent geometric errors and position-independent geometric errors. A method is proposed to identify and measure the position-independent geometric errors of a five-axis machine tool with a tilting head by means of simultaneous multi-axis controlled movements using a double-ball bar (DBB). Techniques for identifying position-independent geometric errors have been proposed by other researchers. However, most of these are based on the assumption that position-dependent geometric errors (such as linear displacement, straightness, and angular errors) are eliminated by compensation, once the position-independent geometric errors have been identified. The approach suggested in this paper takes into account the effect of position-dependent geometric errors. The position-dependent geometric errors are first defined. Path generation for circle tests with two or three simultaneous control movements is then carried out to measure the position-independent geometric errors. Finally, simulations and experiments are conducted to confirm the validity of the proposed method. The simulation results show that the proposed method is sufficient to accurately identify position-independent geometric errors. The experimental results indicate that the technique can be used to identify the position-independent errors of a five-axis machine tool with a tilting head.

The concept of measurement-enabled production is based on integrating metrology systems into production processes and generated significant interest in industry, due to its potential to increase process capability and accuracy, which in turn reduces production times and eliminates defective parts. One of the most promising methods of integrating metrology into production is the usage of external metrology systems to compensate machine tool errors in real time. The development and experimental performance evaluation of a low-cost, prototype three-axis machine tool that is laser tracker assisted are described in this paper. Real-time corrections of the machine tool's absolute volumetric error have been achieved. As a result, significant increases in static repeatability and accuracy have been demonstrated, allowing the low-cost three-axis machine tool to reliably reach static positioning accuracies below 35 μm throughout its working volume without any prior calibration or error mapping. This is a significant technical development that demonstrated the feasibility of the proposed methods and can have wide-scale industrial applications by enabling low-cost and structural integrity machine tools that could be deployed flexibly as end-effectors of robotic automation, to achieve positional accuracies that were the preserve of large, high-precision machine tools.

The measurement of six-degrees-of-freedom (6-DOF) errors of rigid bodies can show the real and accurate spatial pose of those rigid bodies. It plays a major role in precision calibration, spacecraft docking, machining, assembly, etc. In this paper, a four parallel laser-based simultaneous measurement (FPL-SM) method is proposed for measuring 6-DOF errors of rigid bodies with translational motion. First, a FPL-SM device is introduced. Its four laser heads form a rectangle, which is perpendicular to the movement direction of the measured linear displacement. Second, identification formulas for all geometrical errors in rigid bodies with translational motion are presented based on the relative positions of the four lasers. Based on the readings of the four lasers, angular errors and corresponding straightness errors are calculated for the direction of motion around the other two linear motions. As the two parallel sides of the rectangle are in different planes, the straightness errors of the two planes are different. The rolling angular error in the direction is expressed as the difference between the straightness errors of the two planes divided by the distance between the two planes. Six fundamental errors for rigid bodies with translational motion are obtained by four lasers in a single setting of the device. For multiple rigid bodies with mutually perpendicular translational motion, the squareness error is calculated by fitting to the actual direction of motion. Finally, experiments were carried out on the SmartCNC_DRDT five-axis machine tool and 21 geometric errors were determined for three translational axes. Error compensation was carried out using the generated machine tool geometric error data to verify the effectiveness of the proposed FPL-SM method. In addition, geometric errors and thermal errors of the Z axis of the GTI-2740 machine tool are measured based on the FPL-SM method.

Coordinate measuring machines (CMMs) are complex measuring systems that are widely used in manufacturing industry for form, size, position, and orientation assessment. In essence, these systems collect a set of individual data points that in practice is often a relatively small sample of an object. Their software then processes these points in order to produce a geometric result or to establish a local coordinate system from datum features. The subject of CMM evaluation is a broad and multifaceted one. This paper is concerned with the uncertainty in the coordinates of each point within the measuring volume of the CMM. Therefore, a novel method for measurement uncertainty evaluation using limited-size data sets is conceived and developed. The proposed method is based on a Bayesian regularized artificial neural network (BRANN) model consisting of three inputs and one output. The inputs are: the nominal coordinates; the ambient temperature; and the temperature of the workpiece. The output is the measured (actual) coordinates. An algorithm is developed and implemented before training the BRANN in order to map each nominal coordinate associated with the other inputs to the target coordinate. For validation the model is trained using a relatively small sample size of ten data sets to predict the variability of a larger sample size of ninety data sets. The calculated uncertainty is improved by more than 80% using the predicted variability compared to the uncertainty from the limited sample data set.