| Spiral bevel gear is a transmission component with the advantages of high efficiency,stable transmission,and large transmission load.It is widely used in automobile,aerospace,navigation and other fields,and the demand is also very large.The bevel gear machine tool is an important equipment for the production and processing of spiral bevel gears,but during the cutting process,the vibration generated on the tool will affect the surface processing quality of the workpiece and the stability of the cutting process.This paper takes the machining of large spiral bevel gears by forming method as the research object,explores the influence of parameters such as spindle speed,feed per tooth,tool rake angle,edge inclination angle on cutting vibration,and proposes process reliability based on the dynamic characteristics of the machine tool.The evaluation method provides theoretical guidance for actively suppressing cutting vibration and improving the use stability of bevel gear machine tools.Specific research contents include:(1)According to the geometric principle of machining the large wheel of spiral bevel gear by the forming method,the calculation formula of the instantaneous undeformed chip area during tooth milling is deduced.According to the Johnson-Cook model of the material and the bevel cutting theory,the shear strain,shear strain rate and shear stress in the shear zone of the material were deduced.The corresponding simulation program is used to solve the theoretical model,and experiments are designed to verify the theoretical model.(2)A gear milling dynamics model is established for the tool-workpiece system of bevel gear machine tools.The modal parameters such as damping ratio,natural frequency and stiffness coefficient of the dynamic model are obtained by modal hammering experiment.Using Matlab\simulink software,the graphical programming of the dynamic model is realized,and the tooth cutting experiment is designed to verify the dynamic model.(3)The causes of vibration in the machining process of bevel gear machine tools are analyzed,and the influence of parameters such as spindle speed,feed per tooth,tool rake angle,edge inclination angle on cutting vibration is studied based on the milling dynamics model.A prediction model of BP neural network is established,and the sensitivity of parameters affecting cutting vibration is analyzed combined with Garson algorithm.(4)Based on Bayesian theory,the dynamic simulation data and test data were integrated,and the update of the BP neural network prediction model was completed,and the amplitude characteristic value under the extreme working condition was predicted.Combined with the simulated vibration curve on the tool,the realization of Process reliability assessment. |
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