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 

机构地区：[1]Key Lab of Industrial Fluid Energy Conservation and Pollution Control,Qingdao University of Technology,Ministry of Education,Qingdao 266520,China [2]School of Materials Science and Engineering,Xi’an University of Technology,Xi’an 710048,China [3]College of Mechanical Engineering and Automation,Liaoning University of Technology,Jinzhou 121001,China [4]Mechanical Engineering Department,Ahmadu Bello University,Zaria 810106,Nigeria

出　　处：《Chinese Journal of Mechanical Engineering》2024年第5期126-148,共23页中国机械工程学报（英文版）

基　　金：Supported by Special Fund of Taishan Scholars Project(Grant No.tsqn202211179);National Natural Science Foundation of China(Grant No.52105457);Shandong Provincial Young Talent of Lifting Engineering for Science and Technology(Grant No.SDAST2021qt12);National Natural Science Foundation of China(Grant No.52375447);China Postdoctoral Science Foundation Funded Project(Grant No.2023M732826).

摘　　要：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 grinding wheel is established.To examine the impact of changing the grit size of the grinding wheel and grinding depth on workpiece surface roughness,and to validate the accuracy of the model,experiments are conducted.Results indicate that the predicted three-dimensional morphology of the grinding wheel and workpiece surfaces closely matches the actual grinding wheel and ground workpiece surfaces,with surface roughness prediction deviations as small as 2.3%.

关 键 词：Surface topography prediction GRINDING Grinding wheel model Random plane method 

分 类 号：TG580.6[金属学及工艺—金属切削加工及机床]