Position-dependent geometric errors measurement and identification for rotary axis of multi-axis machine tools based on optimization method using double ball bar

Abstract To improve the machine tool accuracy, an integrated geometric error identification and prediction method is proposed to eliminate the positioning inaccuracy of tool ball for a double ball bar (DBB) caused by the rotary axis’ geometric errors in a multi-axis machine tool. In traditional geometric errors identification model based on homogenous transformation matrices (HTM), the elements of position-dependent geometric errors(PDGEs) are defifined in the local frames attached to the axial displacement, which is inconvenient to do redundance analysis. Thus, this paper proposed an integrated geometric error identification and prediction method to solve the uncertainty problem of the PDGEs of rotary axis. First, based on homogeneous transform matrix (HTM) and multi-body system (MBS) theory, The transfer matrix only considering the rotary axes is derived to determine the tool point position error model. Then a geometric errors identification of rotary axis is introduced by measuring the error increment in three directions. Meanwhile the geometric errors of C-axis are described as position-dependent truncated Fourier polynomials caused by fitting discrete values. Thus, The geometric error identification is converted to the function coefficient. Finally, the proposed new prediction and identification model of PDGEs in the global frame are verified through simulation and experiments with double ball-bar tests.

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Geometric characterisation and simulation of position independent geometric errors of five-axis machine tools using a double ball bar

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-015-7711-0 ◽

2015 ◽

Vol 83 (9-12) ◽

pp. 1905-1915 ◽

Cited By ~ 6

Author(s):

Xiaogeng Jiang ◽

Robert J. Cripps

Keyword(s):

Machine Tools ◽

Geometric Errors ◽

Double Ball Bar ◽

Ball Bar ◽

Five Axis

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New identification method for computer numerical control geometric errors

Measurement and Control ◽

10.1177/00202940211010835 ◽

2021 ◽

pp. 002029402110108

Author(s):

Hongtao Yang ◽

Mei Shen ◽

Li Li ◽

Yu Zhang ◽

Qun Ma ◽

...

Keyword(s):

Machine Tools ◽

Geometric Error ◽

Numerical Control ◽

Identification Accuracy ◽

Cnc Machine Tools ◽

Geometric Errors ◽

Cnc Machine ◽

Identification Method ◽

Double Ball Bar ◽

Ball Bar

To address the problems of the low accuracy of geometric error identification and incomplete identification results of the linear axis detection of computer numerical control (CNC) machine tools, a new 21-item geometric error identification method based on double ball-bar measurement was proposed. The model between the double ball-bar reading and the geometric error term in each plane was obtained according to the three-plane arc trajectory measurement. The mathematical model of geometric error components of CNC machine tools is established, and the error fitting coefficients are solved through the beetle antennae search particle swarm optimization (BAS–PSO) algorithm, in which 21 geometric errors, including roll angle errors, were identified. Experiments were performed to compare the optimization effect of the BAS–PSO and PSO and BAS and genetic particle swarm optimization (GA–PSO) algorithms. Experimental results show that the PSO algorithm is trapped in the local optimum, and the BAS–PSO is superior to the other three algorithms in terms of convergence speed and stability, has higher identification accuracy, has better optimization performance, and is suitable for identifying the geometric error coefficient of CNC machine tools. The accuracy and validity of the identification results are verified by the comparison with the results of the individual geometric errors detected through laser interferometer experiments. The identification accuracy of the double ball-bar is below 2.7 µm. The proposed identification method is inexpensive, has a short processing time, is easy to operate, and possesses a reference value for the identification and compensation of the linear axes of machine tools.

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