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Research On Optimization Technology Of Segmental Variable Blank Holder Force Forming

Posted on:2018-12-27Degree:MasterType:Thesis
Country:ChinaCandidate:L HanFull Text:PDF
GTID:2322330542469617Subject:(degree of mechanical engineering)
Abstract/Summary:PDF Full Text Request
Stamping process is one of the main production technologies of automobile panel forming,with the rapid development of plastic forming technology and CAE technology,stamping technology has made great progress.Blank holder force is an important technical parameter of stamping forming,it is difficult to obtain the ideal forming effect by using the blank holder force in the case of the complicated automobile panel.So scholars put forward the segmental variable blank holder force technology,the SVBHF is that the blank holder force changes with the different positions and different stamping time according to certain rules.The difficulty of this technology lies in how to properly partition and determine the reasonable pressure loading curve of each partition.In view of this,this paper puts forward a new method for the partition of the blank holder based on the shrinkage of the edge of the blank,and uses the BP neural network and genetic algorithm to optimize the load curve of the variable blank holder force.The main research contents are as follows:1.Analyse the forming condition of the sheet metal under the condition of the constant blank holder force,and record the shrinkage of edge nodes after sheet metal forming.2.The blank holder is divided into the straight edge section and the fillet section by the shrinkage increment extremum of edge nodes under the condition of the whole constant blank holder force.Then the finite element simulation model is established under the segmental variable blank holder.3.The stamping process is divided into 5 sections,and the blank holder force values at each section of the blank holders are taken as design variables,the change of the thickness of sheet metal is the objective function.By using the BP neural network and genetic algorithm,the reasonable blank holder force curve of each blank holder section is optimized.The forming results are compared respectively with the whole constant BHF,segmental constant BHF and whole variable BHF forming mode.The comparison results show that the key forming quality indexes such as the maximum thickening rate,the maximum thinning rate and the maximum thickness difference of the parts are better than those of the other three methods.
Keywords/Search Tags:SVBHF, BP neural network, genetic algorithm, optimization design
PDF Full Text Request
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