Simulation And Experimental Study On Abrasive Wear Characteristics Of Single Particle Grinding SiC Ceramics

SiC ceramics have many excellent properties and are widely used in automobile,national defense and other fields.However,because of its high hard brittleness and high wear resistance,grinding process will cause serious grinding wheel wear and grinding surface / subsurface damage,so the research on grinding wheel wear characteristics and grinding mechanism under the influence of grinding wheel wear has very high application value.In this paper,based on the theoretical modeling,simulation and experiment of single abrasive grain characterization,the related characteristics of abrasive wear and the influence of surface forming mechanism and subsurface damage formation mechanism of SiC ceramic indentation in the process of single abrasive grain characterization are studied in detail.The main research contents of this paper are as follows:The process and the material removal form of the single abrasive grain are analyzed,the brittle transition condition of the SiC ceramic is determined,the fracture depth analysis model of the surface damage of the SiC ceramic is established on the basis of the crack propagation mechanism in the brittle removal area,The model of the wear rate of the abrasive particles is approximated by the wear-analysis model of the Usui tool.The model and material removal volume model of single grain of abrasive grains under the wear of abrasive particles were established.Combined with the above analytical model parameters,the process of SiC ceramics characterized by single diamond abrasive particles is simulated and analyzed based on the finite element method,and the crack propagation form and material removal form of silicon carbide ceramics are studied.The influence of characterization parameters on crack propagation and marking force is studied by simulation analysis.The dynamic characterization simulation data are extracted,and the static simulation analysis of abrasive wear evolution form is carried out.Based on the wear characteristics of single grain,a reasonable method for characterization of abrasive wear is put forward,three factors(feed speed,grain size,depth of scoring),three-level orthogonal experiment and mixed-level abrasive wear experiment are designed to measure and collect relevant process data.The change rule of the scoring force,the formation mechanism of the scratch surface,the wear of the abrasive grains,the form of wear and the mechanism of its evolution are analyzed by the surface/ sub-surface topography.Based on BP neural network,a prediction model of SiC ceramic abrasive wear rate with single diamond abrasive particle size as input is established.Combined with the above experimental data,the BP neural network is trained and the validity of the prediction model is tested by verification samples.A single diamond abrasive wear prediction system is designed,which can predict abrasive marking force,abrasive wear amount and wear limit time in real time.