Abstract
Micro-fabrication plays an increasingly important role in aerospace, biomedicine and other fields. CVD diamond has great application prospects in the preparation of micro-grinding tools due to its good wear resistance. In this work, the structured CVD diamond micro-grinding tool is proven to have better machining accuracy and wear resistance through the surface roughness and burr size after machining. According to the measured force signal results, the structured CVD diamond micro-grinding tool can reduce the axial force by 20% and the radial force by 10%. The reduction of the axial-to-radial force ratio proves that the structured CVD diamond micro-grinding tool has higher cutting efficiency. The relationship between acoustic emission signal characteristic value and surface roughness is determined by time domain analysis of acoustic emission. Through wavelet transform and machine learning, the wear degree of the common and structured CVD diamond micro-grinding tool is analyzed and predicted, and the accuracy rate is more than 99%.
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