journal article·2026-01Open access

Simulation and experimental study on the self-sharpening mechanism of polycrystalline cBN abrasive grit based on Voronoi diagram

Yejun Zhu, Lin Wang, Zhaoqin Zhang, Maohua Xiao

Abstract

Polycrystalline cBN (PcBN) abrasive grits have a unique microstructure that contributes to the self-sharpening ability of grinding wheels. However, their self-sharpening mechanism is still unknown, resulting in uncontrollable wear. In this article, wear tests of PcBN abrasive grits under different grinding dosages were conducted, and a finite element model of the microstructure of PcBN abrasive grits was developed based on Voronoi diagrams. Then, the effects of undeformed chip thickness and grinding wheel speed on the microcrack evolution are investigated to validate the experimental phenomena while elucidating the self-sharpening mechanism of PcBN abrasive grits. Compared with monocrystalline cBN (McBN) abrasive grits, PcBN abrasive grits are less likely to crack violently under load due to the existence of particle boundaries, and the durability of the grits is significantly improved. When grinding at low speed, the wheel breakage is more severe and self-sharpening cannot be realized. grit damage can be reduced when the grinding speed is higher than 50 m/s. When the undeformed chip thickness is less than 0.5 μm, PcBN abrasive grits expand cracks by crystal penetration fracture. As the undeformed chip thickness increases, the crack propagation pattern gradually changes to intergranular fracture. Although self-sharpening of abrasive grits can be realized by intergranular fracture, fatigue damage also aggravates abrasive wear. In order to improve the self-sharpening of grinding wheels, the characteristics of abrasive grits and fatigue damage must be comprehensively considered.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced machining processes and optimization · Advanced Surface Polishing Techniques · Metal Alloys Wear and Properties

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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