• CN:11-2187/TH
  • ISSN:0577-6686

›› 2006, Vol. 42 ›› Issue (8): 220-223.

• 论文 • 上一篇    下一篇

基于模拟退火的覆盖件回弹预测

李富柱;郭玉琴;王小椿; 宋维   

  1. 徐州师范大学工学院;西安交通大学机械工程学院;海军航空工程学院机械工程系
  • 发布日期:2006-08-15

SPRINGBACK PREDICTION OF COVER PANELS BASED ON SIMULATED ANNEALING ALGORITHM

LI Fuzhu;GUO Yuqin;WANG Xiaochun;SONG Wei   

  1. Technology Institute, Xuzhou Normal University School of Mechanical Engineering, Xi’an Jiaotong University Department of Mechanical Engineering, Naval Aeronautical Engineering Academy
  • Published:2006-08-15

摘要: 从能量逐渐降低使物质系统向新的平衡状态转移的观点出发,根据覆盖件冲压成形后回弹过程与金属退火过程的强烈相似性,提出用模拟退火法对覆盖件进行回弹预测的思想。设计出一种混合模拟退火算法(BFGS-SA)用于解决设计变量数目较多的覆盖件回弹预测问题,该算法将变尺度的局部优化法(Broyden fletcher goldfarb shann, BFGS)与模拟退火法(Simulated annealing, SA)相结合,充分发挥前者局部寻优能力较强、计算效率高、编程简单以及后者通用性好、容易跳出局部最优陷阱以获得高精度全局最优解的优势。并建立相应的优化模型和退火控制策略。通过对实例仿真计算结果与实际测量结果的比较,验证了所提出回弹预测方案的合理性及回弹预测算法的有效性。

关键词: 覆盖件, 回弹预测, 模拟退火, 退火控制策略

Abstract: From the perspective of the energy being decreased gradually in order to make the substance system transfer to a new state of balance, it is suggested that the simulated annealing (SA) is applied to handle the springback prediction problem of cover panels after being formed according to the intense resemblance of this problem with that of the metal annealing. Therefore, a BFGS-SA hybrid algorithm is designed to solve the problem of the springback prediction of cover panels with many design variables. It combines the Broyden fletcher goldfarb shann (BFGS) algorithm with the SA so that take full advantages of each of them, such as the powerful ability of searching the local optimization solution, the higher efficiency, the simple programming for the former and the general applica bility, the great ability of climbing out the local optima to reach a higher accurate global optimal solution for the latter. And the corresponding optimization model and the cooling schedule are established for the BFGS algorithm. By comparing the results of the simulated calculation with those of the practical measurement at the specified points, the rationality of the proposed schedule and the validity of the BFGS-SA algorithm for the springback prediction are verified.

Key words: Simulated annealing, Anneal control strategy, Cover panels, Springback prediction

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