Topography Modeling of Surface Grinding Based on Random Abrasives and Performance Evaluation

作者：Yanbin Zhang, Peng Gong, Lizhi Tang, Xin Cui, Dongzhou Jia, Teng Gao, Yusuf Suleiman Dambatta, Changhe Li · 发表于：Chinese Journal of Mechanical Engineering · 年份：2024 · DOI：10.1186/s10033-024-01081-x · 被引用次数：33 · 研究领域：Advanced machining processes and optimization、Advanced Surface Polishing Techniques、Advanced Measurement and Metrology Techniques

Abstract The surface morphology and roughness of a workpiece are crucial parameters in grinding processes. Accurate prediction of these parameters is essential for maintaining the workpiece’s surface integrity. However, the randomness of abrasive grain shapes and workpiece surface formation behaviors poses significant challenges, and accuracy in current physical mechanism-based predictive models is needed. To address this problem, by using the random plane method and accounting for the random morphology and distribution of abrasive grains, this paper proposes a novel method to model CBN grinding wheels and predict workpiece surface roughness. First, a kinematic model of a single abrasive grain is developed to accurately capture the three-dimensional morphology of the grinding wheel. Next, by formulating an elastic deformation and formation model of the workpiece surface based on Hertz theory, the variation in grinding arc length at different grinding depths is revealed. Subsequently, a predictive model for the surface morphology of the workpiece ground by a single abrasive grain is devised. This model integrates the normal distribution model of abrasive grain size and the spatial distribution model of abrasive grain positions, to elucidate how the circumferential and axial distribution of abrasive grains influences workpiece surface formation. Lastly, by integrating the dynamic effective abrasive grain model, a predictive model for the surface morphology and roughness of the ...