[1]冯莹莹,骆宗安,张宏阁,等.T形管内高压成形过程加载路径的优化方法[J].哈尔滨工程大学学报,2020,41(6):929-936.[doi:10.11990/jheu.201901021]
 FENG Yingying,LUO Zongan,ZHANG Hongge,et al.Optimization method for the loading path of a T tube in the hydroforming process[J].hebgcdxxb,2020,41(6):929-936.[doi:10.11990/jheu.201901021]
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T形管内高压成形过程加载路径的优化方法(/HTML)
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《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
41
期数:
2020年6期
页码:
929-936
栏目:
出版日期:
2020-06-05

文章信息/Info

Title:
Optimization method for the loading path of a T tube in the hydroforming process
作者:
冯莹莹1 骆宗安1 张宏阁2 毛蓝宇1
1. 东北大学 轧制技术及连轧自动化国家重点实验室, 辽宁 沈阳 110819;
2. 一汽轿车股份有限公司, 吉林 长春 130012
Author(s):
FENG Yingying1 LUO Zongan1 ZHANG Hongge2 MAO Lanyu1
1. State Key Laboratory of Rolling and Automation, Northeastern University, Shenyang 110819, China;
2. FAW CAR Co., Ltd., Changchun 130012, China
关键词:
T形管内高压成形加载路径数值模拟正交试验BP神经网络平均性能指标函数智能优化
分类号:
TG394
DOI:
10.11990/jheu.201901021
文献标志码:
A
摘要:
为了研究T形管内高压成形过程加载路径对成形性能的影响,本文对其加载路径的优化方法进行了研究。将背向位移纳入加载路径的主要因素,将加载路径(内压力,轴向进给、背向位移)以三因素图的形式呈现,直观准确的显示加载路径主要因素的相互关系。采用正交试验方法确定加载路径的初始值,将基于遗传算法的BP神经网络控制方法用于优化T形管的加载路径。将支管顶部与背向冲头之间的接触面积纳入成形结果的主要评价因素中,通过建立最大壁厚、最小壁厚、支管高度、支管与背向冲头的接触面积4个主要评价因素的平均性能指标函数,优化了BP神经网络的学习效率,提高了计算精度。模拟结果与实验结果的误差在±5%以内,说明此加载路径优化控制方法具有较高的精度和可行性。

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2019-01-07。
基金项目:国家重点研发计划(2017YFB0305000/04);中央高校基本科研业务专项资金项目(N170704014).
作者简介:冯莹莹,女,副研究员;骆宗安,男,教授,博士生导师.
通讯作者:冯莹莹,E-mail:fengyy@ral.neu.edu.cn.
更新日期/Last Update: 2020-07-22