欢迎访问机床与液压官方网站!

咨询热线:020-32385312 32385313 RSS EMAIL-ALERT
基于离散鲸鱼优化算法的钣金折弯工序优化设计
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:

湖北省教育厅科学技术研究项目(B2020012)


Optimization Design of Sheet Metal Bending Sequence Based on DWOA
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    在折弯工件的整个工艺流程中,操作板料的掉头、翻转次数、各个工步的距离和模具的选择都会影响钣金折弯工序的效率。为此,采用改进的鲸鱼优化算法对折弯工序进行优化设计。对经典鲸鱼优化算法进行改进,重新定义鲸鱼个体以及围猎方式,并引入局部搜索操作增强解的可行性,以减少陷入局部最优解的概率。最后应用于折弯工序问题上,并与已知相关算法分析比较。实验结果表明:使用改进后的离散鲸鱼算法对折弯工序问题进行计算,得出了符合要求的最佳折弯工序方案,求解质量高于对比算法,离散鲸鱼算法在寻找最佳工序方案的问题上有着更佳的全局寻优能力和较快的收敛特性。

    Abstract:

    In the whole process of bending workpiece,the number of turns and flips,the distance of each working step and the selection of the mold will affect the efficiency of the sheet metal bending sequence.Therefore,an improved whale optimization algorithm was used to optimize the design of the bending sequence.The classical whale optimization algorithm was improved,the individual whale and the hunting method were redefined,and the local search operation was introduced to enhance the feasibility of the solution,so as to reduce the probability of falling into the local optimal solution.Finally,it was applied to the bending sequence problem,and was analyzed and compared with the known related algorithms.The experimental results show that the improved discrete whale optimization algorithm (DWOA) is used to calculate the bending sequence problem,and the optimal bending sequence plan that meets the requirements is obtained.The solution quality is higher than the comparison algorithms,and the discrete whale algorithm has better global optimization ability and faster convergence characteristics in finding the best sequence plan.

    参考文献
    相似文献
    引证文献
引用本文

赵云涛,董一帆,李维刚.基于离散鲸鱼优化算法的钣金折弯工序优化设计[J].机床与液压,2023,51(18):102-107.
ZHAO Yuntao, DONG Yifan, LI Weigang. Optimization Design of Sheet Metal Bending Sequence Based on DWOA[J]. Machine Tool & Hydraulics,2023,51(18):102-107

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2023-10-09
  • 出版日期: 2023-09-28