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基于粒子群算法的双辊铸轧工艺优化 被引量：2

Optimizing Processing Parameters for Twin-Roll Strip Casting Using Particle Swarm Optimization
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摘要 针对双辊铸轧过程中凝固终点位置这一关键参数,基于贝叶斯方法的神经网络和理论模型,根据经验模型及熔池断面几何关系建立凝固终点位置数学模型.在化学成分和工艺约束已知的条件下,采用粒子群优化算法针对凝固终点位置这一铸轧过程中的关键因素进行相应的工艺参数的优化计算.铸轧实验结果验证了优化结果的可行性,从而为提高双辊铸轧板形和板厚的控制精度,改善铸带表面质量提供可能. In order to improve the flat,gauge control precision and surface quality of casting strips,processing parameters were optimized based on a kiss point position calculation model（combining a Bayesian neural network and a theoretical model） and using a particle swarm optimization method under given chemical composition and process constraint conditions.Optimized and experimental results showed good agreement.
作者 曹光明 李成刚 刘振宇 高柏宏
机构地区 东北大学轧制技术及连轧自动化国家重点实验室 沈阳机床有限公司
出处 《东北大学学报（自然科学版）》 EI CAS CSCD 北大核心 2011年第5期667-670,共4页 Journal of Northeastern University(Natural Science)
基金 国家自然科学基金资助项目(50734001) 中央高校基本科研业务费青年教师科研启动基金资助项目(N100307006)
关键词 凝固终点 贝叶斯方法 粒子群优化算法 过程工艺优化 kiss point Bayesian method particle swarm optimization method processing parameters optimization
分类号 TP183 [自动化与计算机技术—控制理论与控制工程]
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参考文献11

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二级参考文献4

共引文献86

同被引文献23

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引证文献2

二级引证文献12

东北大学学报（自然科学版）
2011年 第5期

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