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- W4322502667 abstract "CNC machine tools are a measure of national manufacturing and comprehensive national strength and how to reduce CNC machine errors in modern industry has received much attention from all walks of life. The thermal deformation of the feed axis of CNC machine tools is affected by the machine’s structure, installation, material properties, motion position, working conditions, and environmental temperature. Therefore, adopting a single thermal error model to the compensation implementation needs is difficult under changing motion parameters. In this paper, VMC655H is used as the research object and an embedded system is used as the control core. The model classification method is based on the approximate matching of the motion parameters of the thermal error model. Dynamic loading technology is used to fit multiple thermal error models as a technical means to reduce the impact of the machine feed axis’s thermal deformation on the positioning accuracy during the manufacturing process. The thermal error classification model for machine tool feed axes with variable motion parameters in an embedded environment can classify, identify, and load compensation device models within a limited range of motion parameters. This strategy can determine the current operating environment and compensate for the poor adaptability of a single thermal error model. The study of the actual operation effect of the compensation device under this strategy shows that the compensation strategy proposed in this paper can compensate for the thermal deformation of the ball screw feed axis under variable motion, and the X-axis positioning accuracy of its feed system can be improved by 53.11%. This study provides a new idea for the compensation method for thermogenic errors in machine tools." @default.
- W4322502667 created "2023-02-28" @default.
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- W4322502667 date "2023-02-26" @default.
- W4322502667 modified "2023-09-30" @default.
- W4322502667 title "Vertical Machining Center Feed Axis Thermal Error Compensation Strategy Research" @default.
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- W4322502667 doi "https://doi.org/10.3390/app13052990" @default.
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