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Volume 42 Issue 2
May  2022
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Article Navigation >  Diamond & Abrasives Engineering  > 2022  >  42(2): 208-215
LI Kaixuan, LI Jun, XIONG Guanghui, WU Cheng, YU Ningbin, GAO Xiujuan. Flatness prediction of single pendulum polishing based on microelement material removal model[J]. Diamond & Abrasives Engineering, 2022, 42(2): 208-215. doi: 10.13394/j.cnki.jgszz.2021.0116
Citation: LI Kaixuan, LI Jun, XIONG Guanghui, WU Cheng, YU Ningbin, GAO Xiujuan. Flatness prediction of single pendulum polishing based on microelement material removal model[J]. Diamond & Abrasives Engineering, 2022, 42(2): 208-215. doi: 10.13394/j.cnki.jgszz.2021.0116
shu

Flatness prediction of single pendulum polishing based on microelement material removal model

doi: 10.13394/j.cnki.jgszz.2021.0116

  • College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

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  • Received Date: 2021-11-22
  • Accepted Date: 2021-12-22
  • Rev Recd Date: 2021-12-20
    Abstract
  • A microelement material removal model was proposed to explore the influence of single pendulum parameters on the polishing flatness of workpiece. Based on the coupling of velocity and pressure distribution, the model could predict the polishing flatness. Starting from the material removal of single abrasive particle, the model of material removal height of each microelement on the workpiece surface in unit time was established. The velocity of workpiece relative to polishing pad and pressure distribution of workpiece surface was coupled and inserted into the model. According to the initial surface shape of workpiece, the height value of microelement was extracted, and the flatness of the workpiece after polishing was calculated combined with the thickness of microelement material removal. Experiments were carried out to validate the flatness prediction method. The results show that the change trend of the surface shape after simulated polishing is same as actual polishing, and the absolute deviation of flatness PV20 is less than 12.0%. The flatness prediction is reliable.

     

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