Research On Identification Of Key Machining Parameters And Surface Quality Of Blade Belt Grinding

As one of the important processing methods,belt grinding was characterized by a combination of grinding,lapping and polishing functions with excellent grinding surface quality.The surface shape of an aviation blade was usually a complex free-form surface,and most of the materials used were typical difficult-to-machine materials.At the same time,it was necessary to meet the requirements of high efficiency and high precision machining.Machining accuracy and quality would directly affect the performance and service life of the engine and related products,so it would bring many difficulties to machining.As an effective method for machining complex free-form surfaces such as blades,abrasive belt grinding played an important role in improving the processing efficiency and surface quality of blades.However,in the current blade grinding process,the selection of blade grinding parameters was still based on the traditional "trial cutting" and "experience" methods,which were highly dependent on the processing personnel.The machining efficiency was low and it was hard to guarantee the machining quality.In order to achieve the requirements of high precision along with low surface roughness of the workpiece,to get rid of the status quo of relying on manual decision-making,and to achieve reasonable prediction and control of surface quality.This project selects a certain type of TC4 titanium alloy blade as the object,and carries out research on the identification of key machining parameters and the surface quality of blade belt grinding.The research work mainly includes:Identification of key processing parameters for abrasive belt grinding.The grinding process contains many process parameters and the grinding process is complex.This project uses the framework method to represent the process instances in the abrasive belt grinding process.Based on the rough set theory,this project conducts the discretization and attribute reduction of the process parameters,and uses the analytic hierarchy process to assign and recalculate the weights of each feature attributes.So as to rank the grinding process parameters affecting the surface quality and determine the key process parameters in the abrasive belt grinding process.Analysis of the grindability of blade belt grinding and construction of an experimental table.This study analyzes the material properties and the grindability of TC4 titanium alloy,as well as the feasibility of using abrasive belt grinding to process titanium alloy materials.Design and construction of a constant-force belt grinding experiment platform to meet the experimental conditions and verify the effectiveness of the constant-force control software in conjunction with the selected key processing parameters.Experimental program and surface quality analysis of belt grinding.Surface roughness and surface topography were selected as the indexes to evaluate the surface quality.Work out various technological parameters in grinding test,study the influence of abrasive grain size,grinding pressure and linear velocity of abrasive belt on surface roughness by single factor test,and study the influence of multi-factor interaction on workpiece surface roughness by orthogonal test.On this basis,this study optimizes the parameter combination,establishes the surface roughness prediction model,and verifies the accuracy of the prediction model and tests the significance of the regression equation.Experiments on CNC abrasive belt grinding of a certain type of blade.Experiments were carried out on a certain type of TC4 aviation blade to verify the accuracy of the parameter combination optimization and the surface roughness prediction model.The results show that all the corresponding grinding parameters can meet the grade range of surface roughness,and the minimum relative error of the prediction model is 2.16% and the maximum relative error is10.2%,which indicates that the prediction model has certain accuracy.The choice of a reasonable parameters combination and adjusting them accordingly in conjunction with the prediction model,can get the workpiece that meets the requirements,which is of some significance to the actual grinding process.