Multi-machine tools volumetric error generalized modeling and Ethernet-based compensation technique

Xiang, Sitong; Yang, Jing; Fan, Kaiguo; Liu, Hongxing

doi:10.1177/0954405414564407

Cited by 17 publications

(11 citation statements)

References 24 publications

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“…Multibody system theory and the homogeneous coordinate transformation method are common and important theoretical tools for characterizing the mapping relationship between geometric error terms and position and posture vectors. 20,21 Lee et al 22 adopted a C 1 -type continuous function to characterize the PIGEs and PDGEs of a TTTTT-type five-axis machine tool, and the installation errors and PDGEs at different positions were simulated and analysed. Jaroslav 23 analysed special classes of matrices over dual numbers and established a multiaxis machine geometric error model with dual number calculus.…”

Section: Introductionmentioning

confidence: 99%

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

Guo

Tang

Jiang

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part B:

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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.

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Section: Introductionmentioning

confidence: 99%

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

Guo

Tang

Jiang

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part B:

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show abstract

“…The volumetric error has significant effect on the motion accuracy of a machine tool, and severely influences the geometric dimension accuracy of the workpiece, thus, measurement and compensation are required [11][12][13][14][15][16]. Xiang et al [17] developed a volumetric error compensation technique for real-time and simultaneous compensation of the volumetric errors of multiple machine tools by integrating an ethernet distributed numerical control system with a generalized volumetric error kinematic model, which was also developed in this study. Due to the increased importance of integrating metrology systems to machine tools to online compensate volumetric errors of machine tools for improving machining efficiency and accuracy, Wang and Maropoulos [2] developed a real-time volumetric error compensation algorithm to improve the dynamic path accuracy of a machine tool using a laser tracker-assisted 3-axis positioning system.…”

Section: Introductionmentioning

confidence: 99%

Using the Segmented Iterative Learning Control Method to Generate Volumetric Error-Compensated Part Programs for Three-Axis CNC Milling Machine Tools

Yeh

2018

JMMP

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This study proposes using the iterative learning control method to adjust the volumetric error-compensated tool path, where the working volume motion accuracy of three-axis computerized numerical control (CNC) milling machine tools is increased by segmented modification of the part program. As the three-axis CNC milling machine tools generally have volumetric error of working volume, this study refers to the measured and established table of volumetric errors and uses the method of the modifying part program for volumetric error compensation of machine tools. This study proposes using part-program single-block positioning segmented for volumetric error compensation, as the generated compensated part program with multiple compensated blocks can effectively compensate the volumetric error of working volume in the tool moving process. In terms of the compensated tool path computing method, this study uses the iterative learning control (ILC) method and refers to compensated tool path and volumetric errors along the compensated tool path for iterative computation. Finally, a part program with multiple blocks is modified by the converged optimal compensated tool path, in order that the modified part program has higher-precision volumetric error compensation effect. The simulation result shows that the rate of improvement of error of the volumetric error compensation method proposed in this study is 70%.The result of cutting tests shows that the average rate of improvement of the straightness error of the test workpiece is 60%, while the average rate of improvement of height error is 80%. Therefore, the results of simulation and cutting tests can prove the feasibility of using the ILC method for segmented modification of the volumetric error-compensated part programs proposed in this study.

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“…Many researches [3,4] have focused on the prediction of machined workpiece in recent years. But the most of existing prediction methods consider only one or two error types and ignore the inherent characteristics of the machining error data.…”

Section: Introductionmentioning

confidence: 99%

A New Error Prediction Method for Machining Process Based on a Combined Model

Zhou

Zhu

Wang

et al. 2018

Mathematical Problems in Engineering

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Machining process is characterized by randomness, nonlinearity, and uncertainty, leading to the dynamic changes of machine tool machining errors. In this paper, a novel model combining the data processing merits of metabolic grey model (MGM) with that of nonlinear autoregressive (NAR) neural network is proposed for machining error prediction. The advantages and disadvantages of MGM and NAR neural network are introduced in detail, respectively. The combined model first utilizes MGM to predict the original error data and then uses NAR neural network to forecast the residual series of MGM. An experiment on the spindle machining is carried out, and a series of experimental data is used to validate the prediction performance of the combined model. The comparison of the experiment results indicates that combined model performs better than the individual model. The two-stage prediction of the combined model is characterized by high accuracy, fast speed, and robustness and can be applied to other complex machining error predictions.

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Multi-machine tools volumetric error generalized modeling and Ethernet-based compensation technique

Cited by 17 publications

References 24 publications

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

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

Using the Segmented Iterative Learning Control Method to Generate Volumetric Error-Compensated Part Programs for Three-Axis CNC Milling Machine Tools

A New Error Prediction Method for Machining Process Based on a Combined Model

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