Modeled For Surface Quality And Evolution Mechanism In Point Grinding Engineering Ceramics

The point grinding is an emerging machining method with high efficiency and high precision, its machining mechanism is not understood fully in the current. Engineering ceramics is a typical materials of long-lived structural, hard, brittle and difficult to machining. Therefore, it is widely used in military, aerospace, nuclear power and other high-tech field. However, it is certain randomness in machining. It is difficult for the material plastic-brittle removal mechanism, the basic model of high efficiency machining, high quality machining method and technological conditions. It is important academic value and strategic significance.In this paper, point grinding technology will be used for machining engineering ceramics, and the research object are the surface roughness, surface hardness. Based on the machining mechanism, the mathematical model of surface roughness and micro hardness were builded through multi algorithm fusion, the relationship was revealed between surface roughness, micro hardness and the technical parameter. The study results can provide a theoretical basis for improving machining efficiency and controling quality in point grinding engineering ceramic.This work is mainly reflected in the following:(1) Based on the Griffith fracture strength theory, the critical transformation condition of plastic-brittle fracture was obtained by the indentation theory for fluorophlogopite and glass ceramics. The mechanism of material removal and surface formation were studied by point grinding engineering ceramics experiment. The results indicated that the favorable conditions are the low hardness, higher elastic modulus and appropriate process parameters in point grinding. The mechanism of chip and surface forming is brittle and plastic debris coexistence. Material removal forming is lump collapse and powdered chips (microscopic particles) in the point grinding engineering ceramics.(2) Based on the grinding wheel-workpiece interference trajectory kinematic equations in the point grinding, the relationship between the surface roughness model and process parameters was analyzed. By comparing with some roughness models and the test data, an improvement surface roughness model was proposed in point grinding engineering ceramic. And the results were verified by orthogonal experiment. The results showed the accuracy of improvement model was the highest. The concept of relatively extreme error was proposed, and it can test the sensitivity of model vs process factors. The coincidence degree of the model calculated vs experimental value was tested by the standard deviation. The results indicated that the sensitivity of improved model was the highest.(3) Based on the quantum mechanics theory and material composition analysis, the material theoretical hardness and bond hardness were estimated according to first-principles theory. The causes of actual hardness loss were analyzed. Based on the least squares method, a multiple linear regression model was builded about surface microhardness and process parameters, and the statistically significant and correlation were tested for regression equation and regression coefficients. The results indicated that the significance of multiple regression prediction model was high, and it was verified by experiment.(4) Through the vibration test, idle test and point grinding test, the time and frequency domain characteristics of the vibration acceleration signal were analyzed. The vibration characteristic was studied in point grinding ceramic materials. Idling experimental results indicated that the frequency of external excitation force consistented with the spindle speed, therefore, the wheel-spindle system imbalance due to vibration was maximum to influence grinding process. In the point grinding process, a simple single vibration test results indicated that the influence of grinding wheel speed, grinding depth and workpiece speed on vibration spectrum were the obvious.(5) Through simple single-factor test, it were studied such as the relationship between surface roughness and process parameters in point grinding low-expansion glass, the relationship between surface hardness and process parameters in point grinding fluorophlogopite, and the model assumes were proposed. Based on the BP, RBF neural network algorithm, the numerical fitting and model validate were carried out. Based on the univariate numerical fitting, the complex model assumptions of surface hardness and surface roughness were proposed in point grinding. Based on genetic algorithm (GA) and particle swarm optimization (PSO), the complex models were optimized, the accuracy of the model was tested by orthogonal experiment.Finally, the conclusions were described in this article, and according to found problems of experimental and theoretical modeling, suggestions were proposed for next.