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A grinding force prediction model with random distribution of abrasive grains: considering material removal and undeformed chips

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Abstract

Grinding force is an important index for understanding grinding mechanism. In this paper, based on the single grain-grinding experiment, the grinding force under different grinding parameters was studied. Based on the undeformed chip, the grinding force model of multi-grain abrasive was established. Combined with the randomness of grains distribution, the grinding force model was further improved. And the grinding specific energy under different undeformed chip thickness was obtained by single CBN abrasive grain scratch tests. In addition, grinding experiments were carried out under different grinding parameters, and corresponding grinding force was measured. The results show that the grinding specific energy changes with the change of the undeformed chip thickness. For grinding 45 steel with ceramic bond CBN wheel, when the deformation cutting thickness reaches 50 μm, the grinding specific energy tends to 3460 J/mm3. Under the same grinding parameters, the calculated values of grinding force model are in good agreement with the experimental values. Confirmed by further research, the model has better applicability to small cutting depth, slow feed, and low speed cutting models. This study has certain guiding significance for further research on grinding mechanism and characterizing the grinding force.

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Funding

This research is supported by the Natural Science Foundation of Liaoning Province (No. 2021-MS-263), Open Fund of Key Laboratory of Fundamental Science for National Defense of Aeronautical Digital Manufacturing Process of Shenyang Aerospace University (SHSYS-202101), Foundation of Liaoning Province Education Administration (NO. JYT 2020132), and Independent Innovation Special Fund Project of AECC (ZZCX-2019–019).

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Authors and Affiliations

  1. School of Mechatronics Engineering, Shenyang Aerospace University, Shenyang, China

    Xuezhi Wang, QingYao Liu, Yaohui Zheng & Minghai Wang

  2. Key Laboratory of Fundamental Science for National Defense of Aeronautical Digital Manufacturing Process, Shenyang Aerospace University, Shenyang, China

    Xuezhi Wang, QingYao Liu, Yaohui Zheng & Minghai Wang

  3. Beijing Special Engineering and Design Institute, Beijing, China

    Wei Xing

Authors
  1. Xuezhi Wang
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  2. QingYao Liu
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  3. Yaohui Zheng
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  4. Wei Xing
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  5. Minghai Wang
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Contributions

Methodology, formal analysis, investigation, data curation, writing-original draft: Xuezhi Wang; writing-review and editing, supervision: Qingyao Liu; writing-review and editing, supervision: Yaohui Zheng; writing-review and editing, supervision: Wei Xing; methodology: Minghai Wang.

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Correspondence to Xuezhi Wang or Minghai Wang.

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Wang, X., Liu, Q., Zheng, Y. et al. A grinding force prediction model with random distribution of abrasive grains: considering material removal and undeformed chips. Int J Adv Manuf Technol 120, 7219–7233 (2022). https://doi.org/10.1007/s00170-022-09213-0

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