A New Method for Identifying Geometric Errors Inherent to Revolving Axle of Multi-Axis Machine Tool

2011 ◽  
Vol 697-698 ◽  
pp. 262-267
Author(s):  
Guo Fu Ding ◽  
Lei Jiang ◽  
Shao Wei Zhu ◽  
Shu Wen Ma

Geometric errors identification of revolving axle of multi-axis machine tool has encountered a great difficulty in geometric errors compensation. This paper describes a new method to identify geometric errors inherent to revolving axle of multi-axis machine tool based on a ball-bar system. Under RTCP (Rotation Around Tool Center Point) or RPCP (Rotation Around Part Center Point) function, the displacement errors of revolving axle in X, Y and Z direction can be obtained by the ball-bar system respectively at every measurement angle. With the corresponding identification algorithm proposed in this paper, the whole six geometric errors of revolving axle can be identified. This new method is suitable for any type of multi-axis machine tool and without structural constraints. To confirm the validity of the proposed method, an experiment has been conducted on a five-axis machine tool, and the results show that this method is effective and applicable.

2014 ◽  
Vol 941-944 ◽  
pp. 2219-2223 ◽  
Author(s):  
Guo Juan Zhao ◽  
Lei Zhang ◽  
Shi Jun Ji ◽  
Xin Wang

In this paper, a new method is presented for the identification of machine tool component errors. Firstly, the Non-Uniform Rational B-spline (NURBS) is established to represent the geometric component errors. The individual geometric errors of the motion parts are measured by laser interferometer. Then, the volumetric error for a machine tool with three motion parts is modeled based on the screw theory. Finally, the simulations and experiments are conducted to confirm the validity of the proposed method.


2012 ◽  
Vol 271-272 ◽  
pp. 493-497
Author(s):  
Wei Qing Wang ◽  
Huan Qin Wu

Abstract: In order to determine that the effect of geometric error to the machining accuracy is an important premise for the error compensation, a sensitivity analysis method of geometric error is presented based on multi-body system theory in this paper. An accuracy model of five-axis machine tool is established based on multi-body system theory, and with 37 geometric errors obtained through experimental verification, key error sources affecting the machining accuracy are finally identified by sensitivity analysis. The analysis result shows that the presented method can identify the important geometric errors having large influence on volumetric error of machine tool and is of help to improve the accuracy of machine tool economically.


Author(s):  
Jennifer Creamer ◽  
Patrick M. Sammons ◽  
Douglas A. Bristow ◽  
Robert G. Landers ◽  
Philip L. Freeman ◽  
...  

This paper presents a geometric error compensation method for large five-axis machine tools. Compared to smaller machine tools, the longer axis travels and bigger structures of a large machine tool make them more susceptible to complicated, position-dependent geometric errors. The compensation method presented in this paper uses tool tip measurements recorded throughout the axis space to construct an explicit model of a machine tool's geometric errors from which a corresponding set of compensation tables are constructed. The measurements are taken using a laser tracker, permitting rapid error data gathering at most locations in the axis space. Two position-dependent geometric error models are considered in this paper. The first model utilizes a six degree-of-freedom kinematic error description at each axis. The second model is motivated by the structure of table compensation solutions and describes geometric errors as small perturbations to the axis commands. The parameters of both models are identified from the measurement data using a maximum likelihood estimator. Compensation tables are generated by projecting the error model onto the compensation space created by the compensation tables available in the machine tool controller. The first model provides a more intuitive accounting of simple geometric errors than the second; however, it also increases the complexity of projecting the errors onto compensation tables. Experimental results on a commercial five-axis machine tool are presented and analyzed. Despite significant differences in the machine tool error descriptions, both methods produce similar results, within the repeatability of the machine tool. Reasons for this result are discussed. Analysis of the models and compensation tables reveals significant complicated, and unexpected kinematic behavior in the experimental machine tool. A particular strength of the proposed methodology is the simultaneous generation of a complete set of compensation tables that accurately captures complicated kinematic errors independent of whether they arise from expected and unexpected sources.


Author(s):  
Peng Xu ◽  
Benny C. F. Cheung ◽  
Bing Li

Calibration is an important way to improve and guarantee the accuracy of machine tools. This paper presents a systematic approach for position independent geometric errors (PIGEs) calibration of five-axis machine tools based on the product of exponentials (POE) formula. Instead of using 4 × 4 homogeneous transformation matrices (HTMs), it establishes the error model by transforming the 6 × 1 error vectors of rigid bodies between different frames resorting to 6 × 6 adjoint transformation matrices. A stable and efficient error model for the iterative identification of PIGEs should satisfy the requirements of completeness, continuity, and minimality. Since the POE-based error models for five-axis machine tools calibration are naturally complete and continuous, the key issue is to ensure the minimality by eliminating the redundant parameters. Three kinds of redundant parameters, which are caused by joint symmetry information, tool-workpiece metrology, and incomplete measuring data, are illustrated and explained in a geometrically intuitive way. Hence, a straightforward process is presented to select the complete and minimal set of PIGEs for five-axis machine tools. Based on the established unified and compact error Jacobian matrices, observability analyses which quantitatively describe the identification efficiency are conducted and compared for different kinds of tool tip deviations obtained from several commonly used measuring devices, including the laser tracker, R-test, and double ball-bar. Simulations are conducted on a five-axis machine tool to illustrate the application of the calibration model. The effectiveness of the model is also verified by experiments on a five-axis machine tool by using a double ball-bar.


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