• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2024, Vol. 60 ›› Issue (9): 75-85.doi: 10.3901/JME.2024.09.075

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Research on Mechanism and Subsurface Damage Characteristics of SiC Ultrasonic Grinding Based on Material Impact Characteristics

LIANG Fengshuang1, WU Mingyang1, LIU Lifei1,2   

  1. 1. School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin 150080;
    2. College of Mechanical Engineering, Chongqing University of Technology, Chongqing 400054
  • Received:2023-05-06 Revised:2023-10-09 Online:2024-05-05 Published:2024-06-18

Abstract: Silicon carbide is one of the ideal materials for space optical components, but its grinding subsurface will cause serious surface damage, which will affect the production efficiency, performance and service life of optical components. In order to better control the sub-surface damage of ultrasonic grinding of silicon carbide, numerical simulation and experimental research of ultrasonic assistance grinding are carried out, the motion trajectory equation of abrasive particles is established, the influence law of machining parameters on kinematic characteristics is studied, and the influence mechanism of ultrasonic vibration assisted on material removal in grinding process is analyzed. The removal mechanism and subsurface damage characteristics of sic in ultrasonic grinding under the influence of machining parameters are discussed, and the prediction model of subsurface damage depth is established. The results show that the kinematic characteristics of the abrasive particles change periodically and the abrasive particles impact the workpiece periodically. There are three main removal methods in the process of ultrasonic grinding of silicon carbide: transgranular crack tearing the grain and brittle fracture removal, grain boundary crack extending to the surface of silicon carbide leading to single grain shedding, and grain boundary crack extending to the surface of silicon carbide along the grain boundary leading to massive shedding. It has been proved that the prediction accuracy of subsurface damage depth model is better, and the variance between predicted value and detected value is 0.219.

Key words: silicon carbide ceramics, ultrasonic vibration assistance, grinding, subsurface damage

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