• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>ISIJ international >he Optimal Design for the Production of Hot Rolled Strip with Tight Oxide Scale' by Using Multi-objective Optimization
【24h】

he Optimal Design for the Production of Hot Rolled Strip with Tight Oxide Scale' by Using Multi-objective Optimization

机译：多目标优化的“紧密氧化皮热轧带钢生产优化设计”

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

Recently, customers are demanding for hot rolled strip products to have tight oxide scales on the surfaces. Therefore, high finishing rolling temperature, low coiling temperature and fast finishing rolling speed have to be used to obtain tight oxide scale, which is different from conventional controlled rolling. In order to ensure the mechanical properties at the same time, a framework consisting of the Bayesian neural network and multi-objective particle swarm optimization has been established to determine the optimal hot strip rolling parameters. Due to excellent generalization ability, the Bayesian neural network was employed to develop the model for the prediction of mechanical properties of hot rolled automotive beam steels. The accuracy between the measured and predicted values was within ±30 MPa and ±4% for strength and elongation, respectively, providing a reliable model for the optimal process design. By applying multi-objective particle swarm optimization, the optimized hot rolling process was obtained for the production of hot rolled automotive beam steel with "Tight Oxide Scale". Industrial trials have been carried out, which showed good agreement with the optimized hot strip rolling processes. It has been theoretically and practically proven that the optimal process design framework can effectively locate the optimal processing window for hot strip rolling.
机译：近来，客户要求热轧带材产品在表面上具有紧密的氧化皮。因此，必须使用高精轧温度，低卷取温度和快速精轧速度来获得致密的氧化皮，这与常规的受控轧制不同。为了同时确保机械性能，建立了由贝叶斯神经网络和多目标粒子群算法组成的框架，以确定最佳的热轧带钢参数。由于具有出色的泛化能力，因此使用贝叶斯神经网络开发了用于预测热轧汽车梁钢力学性能的模型。对于强度和伸长率，测量值和预测值之间的精度分别在±30 MPa和±4％之内，从而为最佳工艺设计提供了可靠的模型。通过应用多目标粒子群算法，获得了用于生产“致密氧化皮”的热轧汽车钢的优化热轧工艺。已经进行了工业试验，表明与优化的热轧带钢工艺具有良好的一致性。理论和实践证明，最佳工艺设计框架可以有效地定位热轧带钢的最佳加工窗口。

著录项

  • 来源
    《ISIJ international》 |2011年第9期|p.1468-1473|共6页
  • 作者

    Tao JIA; Zhenyu LIU; Hengfa HU; Guodong WANG;

  • 作者单位

    Formerly The State Key Laboratory of Rolling & Automation, Northeastern University, Shenyang, 110819 P R China. Now The Centre for Metallurgical Process Engineering, The University of British Columbia, 309-6350 Stores Rd., Vancouver, BV6T1Z4 Canada;

    The State Key Laboratory of Rolling & Automation, Northeastern University, Shenyang, 110819 P R China;

    The Technical Research Institute, Meishan Steel Company, Nanjing, 210039 P R China;

    The State Key Laboratory of Rolling & Automation, Northeastern University, Shenyang, 110819 P R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    process design; multi-objective optimization; particle swarm algorithm; Bayesian neural network; tight oxide scale;

    机译：流程设计;多目标优化;粒子群算法;贝叶斯神经网络致密氧化皮;

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