| 引用本文: | 郭强,郑燕萍,朱伟庆,晋保荣.基于BP神经网络遗传算法的高强钢成形研究[J].材料科学与工艺,2020,28(2):89-96.DOI:10.11951/j.issn.1005-0299.20180274. |
| GUO Qiang,ZHENG Yanping,ZHU Weiqing,JIN Baorong.Research on high strength steel forming based on BP neural network genetic algorithms[J].Materials Science and Technology,2020,28(2):89-96.DOI:10.11951/j.issn.1005-0299.20180274. |
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| 摘要: |
| 对新材料DP-780高强钢依据国家标准GB/T228.1-2010进行室温拉伸试验,获得材料的力学性能参数；依据冲压成形极限图,进一步提出冲压成形质量评价指标；针对车身侧围板整个冲压制造工艺过程,对不同的工艺参数设计正交试验,并得到试验数据库；根据BP神经网络遗传算法得到最优参数组合,最后经试验验证,满足成形工艺要求并且与数据库结果相匹配。 |
| 关键词: 高强钢 冲压成形 评价指标 正交试验 优化算法 |
| DOI：10.11951/j.issn.1005-0299.20180274 |
| 分类号:TG386 |
| 文献标识码:A |
| 基金项目:国家林业局林业公益性行业科研专项经费项目(201304405). |
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| Research on high strength steel forming based on BP neural network genetic algorithms |
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GUO Qiang1, ZHENG Yanping1, ZHU Weiqing1, JIN Baorong2
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(1.Department of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China;2.Nanjing Automobile Stamping Parts Co., Ltd, Nanjing 211100, China)
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| Abstract: |
| Based on the national standard GB / T228.1-2010, the room temperature tensile test was carried out on the new material DP-780 high strength steel, and the mechanical property parameters of the material were obtained. According to the stamping limit diagram, the evaluation index of stamping quality was put forward. On the basis of the whole stamping process of the body side panel, the orthogonal test was designed for different process parameters, and the test database was obtained. By utilizing BP neural network genetic algorithm, the optimal parameter combination was obtained. Finally, experiments verified that the combinationmet the requirements of forming process and matched with the database results. |
| Key words: high strength steel stamping forming evaluation index orthogonal test optimization algorithm |
