Experimental research of high quality grinding technology on SiC based on grinding force

Qiancai Wei; Lian Zhou; Xianhua Chen; Shijie Zhao; Nan Zheng; Jie Li; Jian Wang

doi:10.1117/12.2553046

31 January 2020 Experimental research of high quality grinding technology on SiC based on grinding force

Qiancai Wei, Lian Zhou, Xianhua Chen, Shijie Zhao, Nan Zheng, Jie Li, Jian Wang

Proceedings Volume 11427, Second Target Recognition and Artificial Intelligence Summit Forum; 114273M (2020) https://doi.org/10.1117/12.2553046
Event: Second Target Recognition and Artificial Intelligence Summit Forum, 2019, Changchun, China

Abstract

In order to improve the grinding quality and efficiency of SiC elements, the influence of grinding parameters on the grinding quality was studied by using 2MK1760 ultra-precision surface grinder. Based on the surface roughness and surface precision, the relationship between grinding volume and grinding force of metal bonded and resin bonded diamond grinding wheels was researched, and it was obtained that the metal bonded grinding wheels could maintain enough sharpness during a large amount of grinding removal. The grinding force was used to characterize the grinding wheel wear, and through experiments studied the relationship between grinding parameters (including grinding depth) and the SiC material removal volume after grinding wheel one-time dressing. The results showed that different grinding depth will not affect the grinding wheel life under the same other conditions. On the basis of technological experiments, aiming at optimizing grinding efficiency and quality, resin bonded plane grinding wheel was used to grind SiC elements with three diameters of 75mm, 150mm and 320mm, and very small surface precision (PV=3.758μm) and surface roughness (RMS=35.472nm) could be obtained.

Citation Download Citation

Qiancai Wei, Lian Zhou, Xianhua Chen, Shijie Zhao, Nan Zheng, Jie Li, and Jian Wang "Experimental research of high quality grinding technology on SiC based on grinding force", Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 114273M (31 January 2020); https://doi.org/10.1117/12.2553046

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