Study On Metal Flow And Residual Stress In Blade Precision Forging

Blade is a kind of thin-walled part with complex spatial curved surface.As a key part of aeroengine,the material used is expensive and difficult to deform.At present,precision forging technology is mostly used to process the blade.However,in the forming process of thermal mechanical coupling,the complex characteristics of blade shape not only make the metal flow law in the forging process difficult to know,but also lead to different forces on the blades,which can not avoid stress concentration in the forging process,often leading to early failure of components during the working period.Therefore,it is of great significance to study the metal flow and residual stress in the precision forging process of Aeroengine Blades,so as to improve the performance of Aeroengine Blades and prevent defects.Taking an aeroengine blade as an example,according to the modeling characteristics of the blade,through calculation and analysis,the relevant dimensional parameters of blade blank and die balance angle,die pressure center,die parting surface,die rough groove and rough bridge are obtained,and the three-dimensional geometric models of the aeroengine blade,its upper and lower dies and blank are established based on the proe software.Through the definition of geometric model,material model,friction model,thermodynamic parameters,pressure equipment,mesh division,etc.,the TC4 titanium alloy blade precision forging finite element model is established.Based on the basic theory of rigid viscoplastic finite element,the threedimensional numerical simulation of blade precision forging process is carried out with the help of simufact.Forming software.The distribution information of stress field,strain field and temperature field is obtained.The effects of the precision forging process parameters,such as the speed of the upper die,the temperature of the blank,the temperature of the die and the friction coefficient,on the metal flow of the blade surface were studied.The results show that the metal flow velocity in the blade tenon area is less affected by the process parameters,and the change of the flow velocity is not significant,and the flow velocity is close to 0.The metal flow velocity near the joint of blade body and tenon is greatly affected by process parameters.The increase of billet temperature,upper die speed and friction coefficient can increase the metal flow velocity,while the increase of die temperature will reduce the metal flow velocity.The residual stress of blade surface was measured by X ray diffraction technology,and the test results were compared with the numerical simulation results of corresponding positions.Through the orthogonal test of four factors and three levels numerical simulation,the significance degree of the above four precision forging process parameters on the maximum residual stress of blade precision forging is obtained,and the optimal combination of process parameters is obtained by range analysis.The results show that the error between the experimental results and the numerical simulation results is smaller,which indicates that the numerical simulation results of simmanufacture.Forming are more ideal.For the maximum residual stress of blade precision forging,the significance degree of each process parameter is as follows: die temperature > upper die speed > billet temperature > friction coefficient.The optimal combination of process parameters is as follows: mould speed is 40mm/s,billet temperature is 960?,mould temperature is 300?,friction coefficient is 0.1.Finally,using the test data obtained from numerical simulation as samples,taking these four precision forging process parameters as input parameters,taking the maximum residual stress of blade precision forging as output prediction target value,three mathematical models of response surface,BP neural network and GA-BP neural network are established successively,and the prediction effect of the three models is compared and analyzed.The results show that the maximum relative errors between the prediction results and simulation results of the three models are 5.74%,5.15% and2.71%,respectively.Therefore,it is more reliable to use GA-BP neural network to predict the maximum residual stress of blade precision forging.