基于砂轮表面磨粒特性的磨削表面粗糙度建模

Modeling of Ground Surface Roughness based on the Grinding Wheel Tomography

为了预测磨削表面粗糙度和提升磨削质量,引入概率分布的理论对修整后砂轮表面磨粒尺寸、形状和突出高度进行统计学描述,分析磨削过程中砂轮的运动学和材料微观去除过程,提出了基于砂轮表面磨粒特性和磨削工艺参数的磨削表面轮廓和表面粗糙度预测模型,并开展SiC陶瓷磨削实验进行了验证。结果表明砂轮修整后的磨粒成圆锥形,顶角服从N(106,15)的正态分布,而磨粒的突出高度分布可借助瑞利分布描述,采用测量的磨粒特征构建虚拟砂轮,对磨粒加工区域的材料去除后可以得到磨削表面轮廓并计算得到表面粗糙度;相同砂轮线速度情况下,表面粗糙度随进给速度和磨削深度的增加而增加,且工件进给速度较磨削深度对表面粗糙度的影响更大,模型预测表面粗糙度与实验结果间误差在10%以内,实现了对磨削表面粗糙的准确预测,同时该模型也可指导具有微织构的磨削功能表面的设计。

In order to predict the ground surface roughness(Ra)and improve the ground surface quality,the probability and statistics theory were used to describe the grits′size,shape,and protrusion height after dressing.Combining with the analysis of the kinematics and material removal process in micro scale,a model to predict grinding surface profile and Ra was proposed,which was validated by the SiC ceramic grinding experiments.The results indicated that the grit after dressing is in cone shape and the apex angle followed normal distribution N(106,15).The grit protrusion height can be described by using Rayleigh distribution.The surface profile and Ra can be gained by using the virtual grinding wheel,built base on the grit statistic model,to removal interacted material.With the same vs,the Ra increase with the increase of vw and a p.And Ra is more sensitive with the changing of vw.The error between modeling and experiment is within 10%,which indicates that the model can be used to predict the Ra accurately.Besides,this model can be used to instruct the design of micro texture in the ground surface.