• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Materials & design >Prediction of the mechanical properties of the post-forged Ti-6Al-4V alloy using fuzzy neural network
【24h】

Prediction of the mechanical properties of the post-forged Ti-6Al-4V alloy using fuzzy neural network

机译：应用模糊神经网络预测后锻Ti-6Al-4V合金的力学性能

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Isothermal compression of the Ti-6Al-4 V alloy was conducted at a 2500 t isothermal hydrostatic press, and the mechanical properties including ultimate tensile strength, yield strength, elongation and area reduction of the post-forged Ti-6Al-4 V alloy were measured at a ZWICK/Z150 testing machine. A fuzzy neural network (FNN) was applied to acquire the relationships between the mechanical properties and the processing parameters of post-forged Ti-6Al-4 V alloy. In establishing those relationships, the forging temperature, strain and strain rate were taken as the inputs, whilst the ultimate tensile strength, yield strength, elongation and area reduction were taken as the output respectively. The predicted results using the present FNN model is in a good agreement with the experimental data of the post-forged Ti-6Al-4V alloy, and the optimum processing parameters can be quickly and conveniently selected to achieve the desired mechanical properties by means of the prediction based on the fuzzy neural network model.
机译：在2500 t等静压机上对Ti-6Al-4 V合金进行等温压缩，其力学性能包括锻造后的Ti-6Al-4 V合金的极限拉伸强度，屈服强度，伸长率和减小的面积。在ZWICK / Z150测试机上测量。应用模糊神经网络（FNN）来获取后锻Ti-6Al-4 V合金的力学性能与加工参数之间的关系。在建立这些关系时，将锻造温度，应变和应变率作为输入，而将极限抗拉强度，屈服强度，伸长率和面积减小率作为输出。使用当前FNN模型的预测结果与后锻Ti-6Al-4V合金的实验数据非常吻合，并且可以通过以下方法快速方便地选择最佳加工参数以实现所需的机械性能。基于模糊神经网络模型的预测。

著录项

  • 来源
    《Materials & design》 |2010年第7期|p.3282-3288|共7页
  • 作者

    Weixin Yu; M.Q Li; Jiao Luo; Shaobo Su; Changqing Li;

  • 作者单位

    School of Materials Science and Engineering, Northwestern Polytechnical University, Xi'an 710072, PR China;

    rnSchool of Materials Science and Engineering, Northwestern Polytechnical University, Xi'an 710072, PR China;

    rnSchool of Materials Science and Engineering, Northwestern Polytechnical University, Xi'an 710072, PR China;

    rnXi'an Aviation Engine Company Limited, Xi'an 710021, PR China;

    rnXi'an Aviation Engine Company Limited, Xi'an 710021, PR China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    titanium alloy; forging; mechanical properties; fuzzy neural network;

    机译：钛合金锻造;机械性能模糊神经网络;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号