Prediction of surface topography in face gear grinding based on dynamic contour interferometric sampling method

Considering the influence of manufacturing parameters, precisely predicting the post-grinding tooth surface topography is of great significance for improving transmission performance and service life of face gear transmission. However, it faces numerous challenges in practical applications, encompassing factors like abrasive grain size, grain distribution, grinding wheel inclination, and machine tool vibrations. Simultaneously, the establishment of prediction models presents complexities and precision-related difficulties. To predict the tooth surface topography more accurately, this paper proposes a method for predicting surface topography of face gear grinding based on dynamic contour interference sampling. Based on Hertzian contact theory, coupled with abrasive grain interference sampling, the motion trajectories of abrasive grains within discrete grinding width intervals are simulated. Thus, by considering the overlap regions of grinding width between adjacent grinding trajectories, a more accurate prediction of tooth surface topography is achieved. The method delves deeply into the impact of grinding depth on the deformation patterns within the grinding contact region. To validate the accuracy of the proposed method, face gear grinding experiments were designed and conducted, with the experimental results being compared against the predicted outcomes. The experimental results indicate that the topography prediction model, which accounts for grinding trajectory interference, closely aligns with the actual tooth surface topography.