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Analysis of the critical Stick–slip velocity of CNC machine tool combining friction parameters identification and dynamic model

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Abstract

Stick–slip is a negative phenomenon caused by friction in servo feed systems, which is particularly prominent in low-speed and heavy-load conditions. At present, most research on the critical Stick–slip velocity ignores higher-order terms of the equivalent damping ratio; the calculation accuracy is greatly reduced when the system has a large equivalent damping ratio. To solve it, firstly, an improved Stribeck model based on the least squares genetic algorithm is proposed for friction identification; meanwhile, the identification of shape parameters of the traditional Stribeck model is extended instead of empirical values. Then, an improved method of the critical Stick–slip velocity based on the dynamic model is constructed, and the influence of the higher-order term of the equivalent damping ratio on the critical velocity identification accuracy is analyzed. Finally, this method is verified by the computerized numerical control end-face cylindrical grinder with a hard guideway. The friction force identification error of the proposed method is reduced by 10% compared with the traditional method, and the error of the critical Stick–slip velocity by retaining the higher-order term is reduced by 37% compared with the critical Stick–slip velocity by ignoring the higher-order term.

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Funding

This paper is supported by the National High-Quality Development Project of China (no. TC210H03A-04) and the Major Science and Technology Projects of Hubei Province (no. 2020AGA018).

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Contributions

Jianzhong Yang: resources and project administration. Hao Zhou: formal analysis, methodology, investigation, and writing—original draft. Shuo Li: data curation and software. Jihong Chen and Hua Xiang: conceptualization and supervision.

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Correspondence to Hua Xiang.

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Yang, J., Zhou, H., Li, S. et al. Analysis of the critical Stick–slip velocity of CNC machine tool combining friction parameters identification and dynamic model. Int J Adv Manuf Technol 131, 1849–1865 (2024). https://doi.org/10.1007/s00170-024-13202-w

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