Numerical Simulation And Optimization Of Unsymmetrical Y-shaped Tube In Hydroforming Process

Hydroforming is an advanced technology characterized by lightweight and integrity,which people are paying more attention to at present. Unsymmetrical Y-shaped tube hydroforming is applied broadly and it is a difficult point as well. The forming process is very complicated and related to many factors such as loading path,friction condition,Blanking size,corner radius and so on. Among these factors, the success of hydroforming is largely depended on the selection of the loading paths: axial feeding versus time,internal pressure versus time,counter punch versus time.In this dissertation,a aluminum alloys Tube by internal high pressure forming was used as investigated target. The FEA model of whole process was set up. the tube had been divided into three different deformation stages according to different features of deformation and loading action through numerical simulation. After deformation , the result revealed the rule of material flow,stress strain state and thickness distribution of unsymmetrical Y-shaped tube. Afterwards,friction coefficient and corner radius were also studied,and elicit their infection disciplinarian curve. By means of orthogonal test,the influence of loading paths of process parameters (axial feeding, internal pressure, counter punch feeding) was studied.Results of linear loading paths showed that appropriate selection of parameters, reasonable interval and match are very important. Results of dual-linear loading paths showed that a proper dual-linear loading path could achieve a much better forming quality. At last,aiming at the three different deformation stages of Y-shaped tube , this paper presented a multi-linear loading path through trial-and-error which is better than the linear and dual-linear.As to the problem of process parameters match, by means of Neural Network toolbox and Genetic Arithmetic toolbox, the optimization match of linear and dual-linear loading paths were realized. Results showed that combined use of Neural Network and Genetic Arithmetic is a stable, feasible and intelligent method to solve the process parameters optimization problem in IHF. After that optimization method of combined fuzzy control and feed-back-simulation was studied primarily. By adaptive feed-back control strategy, failure indicators obtained from the simulation results were used as the input of the fuzzy logical control,and the output sets of the fuzzy logical control are used for adjusting the loading path.