Abstract
For the ultra-precision turning machine, the spindle system is a core component and plays a decisive role in precise machining. The unbalancing state in the spindle can degrade the quality of the machining surface. Therefore, the spindle system must be exceptionally well balanced before processing. In this paper, we proposed a high accuracy spindle balance method, which adopts the real-time data in the CNC system and combines with disturbance observer (DOB) to estimate the unbalancing vector without any extra sensors. Moreover, this method takes full advantage of the ultra-precision machine structure, the high precision grating, and the high-performance motor servo system to achieve high accuracy measurement for the spindle unbalancing. According to the experimental results, the proposed method accuracy is up to G0.0073, which is at least three levels greater than the highest official ISO balancing quality grade G0.16. In the cutting experiments, the PV value reduce to 0.207 μm from 0.528 μm with upgrading the spindle balance grade to G0.01024 from G0.16, verifies the accuracy of the spindle dynamic balancing method from the practice side.
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Acknowledgements
The authors sincerely thank the Institute of Machinery Manufacturing Technology for providing a comprehensive measurement instrument for surfaces and an ultra-precision machine tool for the experiments.
Funding
This work is supported by Science Challenge Project (No. TZ2018006), National Natural Science Foundation of China (Grant No. 52005460), and National Key R&D Program of China (Grant No. 2020YFB2007600).
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Xiufeng Liu and Wei Wei conceived of the presented idea. Wei Wei designed the experiment software. JinChun Yuan, Yuxuan Tao, and Yuheng Li carried out the experiments. Xiufeng Liu wrote the manuscript. Yu Huang conducted the experiments and revised the manuscript.
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Liu, X., Wei, W., Yuan, J. et al. A High Accuracy Method for the Field Dynamic Balancing of Rigid Spindles in the Ultra-Precision Turning Machine. Int. J. Precis. Eng. Manuf. 22, 1829–1840 (2021). https://doi.org/10.1007/s12541-021-00585-z
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DOI: https://doi.org/10.1007/s12541-021-00585-z