| 基于粒子群优化算法的热轧厚板工艺性能优化 |
| |
| 引用本文： | 谭文,刘振宇,吴迪,刘相华,王国栋. 基于粒子群优化算法的热轧厚板工艺性能优化[J]. 轧钢, 2007, 24(1): 15-18 |
| |
| 作者姓名： | 谭文 刘振宇 吴迪 刘相华 王国栋 |
| |
| 作者单位： | 东北大学轧制技术及连轧自动化国家重点实验室,辽宁,沈阳,110004 |
| |
| 基金项目： | 国家自然科学基金;教育部新世纪优秀人才支持计划 |
| |
| 摘 要： | 为改善热轧厚板的强度和屈强比，结合粒子群优化算法，利用神经元网络建立了粗轧开轧温度、中间坯厚度、终轧温度、终冷温度及冷却速率等生产工艺参数与钢板强度的关系模型，并进行了优化。优化结果与实验室热轧实验及工业试生产结果的对比表明，本模型能有效地优化厚板生产过程的工艺参数，从而为最优工艺或柔性化生产工艺的设计提供依据。
|
| 关 键 词： | 热轧厚板 神经网络 粒子群优化 性能 |
| 文章编号： | 1003-9996(2007)01-0015-04 |
| 修稿时间： | 2006-09-06 |
Optimization of Processing Parameters -properties Using Particle Swarm Optimization (PSO) in Hot Plate Rolling |
| |
| TAN Wen,LIU Zhen-yu,WU Di,LIU Xiang-hua,WANG Guo-dong. Optimization of Processing Parameters -properties Using Particle Swarm Optimization (PSO) in Hot Plate Rolling[J]. Steel Rolling, 2007, 24(1): 15-18 |
| |
| Authors: | TAN Wen LIU Zhen-yu WU Di LIU Xiang-hua WANG Guo-dong |
| |
| Affiliation: | The State Key Lab. of Rolling and Automation, Northeastern University, Shenyang 110004, China |
| |
| Abstract: | A model for processing and properties optimization based on artificial neural network and PSO(Particle Swarm Optimization) algorithm was proposed.In order to obtain the desired strength and lower yield/strength ratio,the relationship of plate strength and parameters,such as rough rolling temperature,temperature-holding thickness,finish rolling temperature,finish cooling temperature and cooling rate were establised and optimized.The experimental results and industrial trials showed that the optimized results were in good agreements with the experimental ones,The model can be applied to the optimal design for processing parameters in plate rolling. |
| |
| Keywords: | hot rolled heavy plate neural network particle swarm optimization property |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
