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Title:Optimization on stamping process of vehicle suspension longitudinal arm based on improved flower pollination algorithm
Authors: Liu Baosheng  Deng Sanpeng 
Unit: Tianjin Transportation Technical College Tianjin University of Technology and Education 
KeyWords: suspension longitudinal arm  stamping  cracking critical state  improved flower pollination algorithm  thinning rate 
ClassificationCode:TG386
year,vol(issue):pagenumber:2021,46(11):130-136
Abstract:

 In order to reduce the thinning rate of vehicle suspension longitudinal arm in the stamping and improve the processing qualification rate of products, the optimizated method of stamping process parameters based on flower pollination algorithm was proposed, and the 3D model and the stamping process of suspension longitudinal arm were introduced. Then, the distributions of equivalent stress and thickness in the critical state of cracking were analyzed by finite element simulation, and the critical location of cracking was determined. Furthermore, the optimization model was established with the goal of reducing the thinning rate of dangerous locations, the upper die pressure and friction coefficient were chosen as the optimization parameters. Optimal Latin hypercube sampling was used to design eighty groups of experiment, and BP neutral network structure with two inputs and one output was established to fit the nonlinear relationship between process parameters and quality parameters. Finally, the global search method of flower pollination algorithm was improved to enhance the search ability of the algorithm, and the optimal parameters combination was obtained by using the improved flower pollination algorithm to solve the optimization model. It is clarified that after optimization, the average thickness of staming parts for suspension longitudinal arm at the dangerous location is 1.637 mm, the standard deviation is 0.091 mm, and the product qualification rate increases from the current 60% to 97%.

Funds:
国家青年自然科学基金资助项目(61301040)
AuthorIntro:
作者简介:刘宝生(1974-),男,硕士,副教授,E-mail:284078387@qq.com
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