Correlation assessment and modeling of intra-axis errors of prismatic axes for CNC machine tools

Mechta, Ahlem; Slamani, M.; Zaoui, Moussa; Mayer, Josef; Châtelain, Jean-François

doi:10.1007/s00170-022-09074-7

Cited by 2 publications

(2 citation statements)

References 48 publications

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“…The proposed method can effectively reduce the error, and then improve the machining accuracy. Mechta et al [11] put forward an evaluation method for the axis error of CNC, and evaluated the effectiveness of the error evaluation method through comparative analysis. The error evaluation method proposed in the study has high accuracy and can accurately predict the axis error of CNC.…”

Section: Related Workmentioning

confidence: 99%

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Intelligent CNC control with improved adaptive thermal error compensation model

Shen,

Yang

2023

J. vibroeng.

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The thermal errors (TE) of computer numerical control (CNC) in workshop production seriously reduces the productivity. Therefore, to improve the productivity of CNC and enhance production intelligence, an improved adaptive TE compensation model (TECM) is proposed. The model is based on an online temperature measurement system (OTMS), which improves the adaptive learning rate of back-propagation neural network (BPNN) for temperature prediction. Finally, the correlation value between temperature changes and TEs is used for thermal error compensation. The performance verification of the model shows that the proposed OTMS can achieve effective temperature acquisition and processing, and the prediction ability of the improved BPNN is significantly higher than that of other prediction algorithms. Finally, it is found in the test that the improved adaptive TECM can reduce the contour error of workpiece machining to within 0.02×10-3 mm, the machining accuracy of CNC is significantly improved. The above results show that using the improved adaptive TECM can promote the intelligent development of CNC and improve their machining accuracy, which is of great significance to the development of workshop manufacturing.

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Section: Related Workmentioning

confidence: 99%

“…Therefore, to improve the convergence speed of the BPNN, it is proposed to use the learning rate training to improve the BPNN, as shown in Eq. (11):…”

Section: Adaptive Tecmmentioning

confidence: 99%

Intelligent CNC control with improved adaptive thermal error compensation model

Shen,

Yang

2023

J. vibroeng.

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Organization and Application of Statistical Modeling

2023

Deterministic and Stochastic Approaches in Computer Modeling and Simulation

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The object of this chapter is principles of organization of statistical modeling and form of its applications. In this reason, the first section discusses the essence of the statical approach and presents the main form for its application. A summary of published research is made to clarify the features of the statistical models and their role in scientific research. The second part is devoted to mathematical statistics, with a brief presentation of basic concepts such as simple and statistical order, statistical estimates, numerical characteristics, and basic methods used in statistical approach. Particular attention is paid to the method of least squares applied in determining the statistical estimates. In the third part, the characteristic surface is presented and the two main groups of statistical models—univariate and multivariate—are discussed. Realization of statistical experiments is discussed in the last part, starting with presentation of a program application for statistical analysis organization and continuing with several concrete examples of regression models.

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Correlation assessment and modeling of intra-axis errors of prismatic axes for CNC machine tools

Cited by 2 publications

References 48 publications

Intelligent CNC control with improved adaptive thermal error compensation model

Intelligent CNC control with improved adaptive thermal error compensation model

Organization and Application of Statistical Modeling

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