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材料导报  2022, Vol. 36 Issue (13): 20110127-12    https://doi.org/10.11896/cldb.20110127
  金属与金属基复合材料 |
“人工智能+有限元”模型在轧制领域的研究进展
王楷, 梅瑞斌*
东北大学轧制技术及连轧自动化国家重点实验室,沈阳 110819
On the Research and Application of “Artificial Intelligence Plus Finite Element” Models in the Field of Rolling
WANG Kai, MEI Reibin*
State Key Laboratory of Rolling and Automation, Northeastern University, Shenyang 110819, China
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摘要 随着轧制工业的不断发展,轧制早已不再局限于获得一定尺寸和形状的工件,而是侧重于使金属材料获得所需的微观组织和力学性能。为实现这一目标,对轧制过程中的轧制参数进行控制是必不可少的。而轧制参数的在线控制是通过结合现代的计算机技术和优良的轧制计算模型,在轧制生产过程中实时监控轧制参数,进而进行实时调节。基于这一手段,轧制的生产效率和产品质量将大大提高。因此构建计算精度高、速度快的轧制计算模型是当前轧制领域的研究热点。
随着对轧制质量要求的不断提高,基于传统理论的数学解析模型由于简化程度高,已不能满足准确描述和分析轧制过程变形、温度、材料、组织等强非线性耦合关系的需求。轧制属于金属塑性加工,计算为大应变弹塑性问题。涉及众多几何以及物理上的非线性问题。针对这些问题,有限元模型虽然有足够高的求解精度,但是其计算时间长的缺点成为了制约其实现在线应用的屏障。近年来,随着计算机技术的高速发展、算法的更替以及参数预测模型基础理论的完善,人工智能和有限元技术在轧制领域的应用越来越多,尤其是“人工智能+有限元”预测模型结合了人工智能模型和有限元模型各自的优势,同时具备计算速度高、泛化能力强的优点,在众多混合式模型中较好地体现了轧制过程在线预测和控制的要求。
本文在对目前轧制领域数学模型、有限元模型、人工智能模型及混合模型研究进展进行综述的基础上,对比了三种模型各自的优缺点,并分别对其各自的改进措施进行了总结。结合目前的研究成果,得出了构建混合模型的必要性。着重对轧制过程中人工智能融合有限元技术加以介绍,阐述了“人工智能+有限元”模型的进步之处,并对今后的发展趋势进行展望。
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王楷
梅瑞斌
关键词:  轧制  在线计算  数学模型  有限元  人工智能    
Abstract: With the continuous development of industry,rolling is no longer limited to obtaining a certain size and shape of the workpiece, but focuses on obtaining the required microstructure and mechanical properties. To achieve this goal, the control of rolling parameters in the rolling process is essential. The on-line control of rolling parameters is using the method combining computer technology and rolling calculation model,which can obtain real-time rolling value parameters in the rolling production process and then achieve real-time adjustment. This method will greatly improve the rolling efficiency and product quality. Therefore, the construction of rolling calculation model with high calculation accuracy and fast calculate speed is a research hotspot in the current rolling field.
With the continuous improvement of rolling quality requirements, due to the simplification of mathematical analytical model based on traditional theory, it cannot meet the requirements of strong nonlinear coupling relationships, such as deformation, temperature, material and microstructure in rolling process. Rolling belongs to metal plastic processing. Its calculation is a large strain elastic-plastic problem. It involves many geometric and physical nonlinear problems. Aimed at these problems, the finite element model is precise, but the disadvantage of long calculation time has become the barrier to on-line control. In recent years, with the rapid development of computer technology, the replacement of algorithms and the improvement of the basic theory of parameter prediction model, artificial intelligence and finite element technologies have been applied in the field of rolling widely. In particular, the ‘Artificial intelligence + Finite element’ prediction model combines the advantages of artificial intelligence model and finite element model, and has the superiority of high calculation speed and strong generalization ability. It better reflects the requirements of online prediction and control of rolling process.
On the basis of summarizing the research progress of mathematical model, finite element model, artificial intelligence model and hybrid model in rolling field, this paper compares the advantages and disadvantages of three models, and summarizes their improvement measures respectively. Combined with the current research results, this paper makes a conclusion that the constructing a hybrid model is very important. It focuses on the model through the introduction of artificial intelligence and finite element technology in rolling process, emphasizes the progress of this hybrid model and looks forward to its future development trend.
Key words:  rolling    online calculation    mathematical model    finite element    artificial intelligence
出版日期:  2022-07-10      发布日期:  2022-07-12
ZTFLH:  O242.21  
基金资助: 河北省自然科学基金钢铁联合基金项目(E2018501016);辽宁省科学技术基金项目 (20170520314)
通讯作者:  * meiruibin@neuq.edu.cn   
作者简介:  王楷,2019年6月在中北大学材料科学与工程学院材料成型及控制工程专业获得工学学士学位。同年考入东北大学材料科学与工程学院材料科学与工程专业,进行硕士研究生阶段的学习。研究方向为轧制在线有限元模型的构建与仿真系统的开发。熟悉机械设计制造、有限元模拟仿真、模具设计加工、材料组织性能分析等领域。曾在多个企业进行有限元模拟仿真等方面的实习工作。
梅瑞斌,2009年在东北大学轧制技术及连轧国家重点实验室材料加工专业获得工学博学位。现任东北大学副教授。主持完成多项省市级项目,作为主要参与人参加完成国家基金重点项目1项、面上项目1项、国际合作项目1项。以第一作者和通讯作者发表学术论文50余篇,其中SCI、EI检索30余篇,获得国家发明专利9项。
引用本文:    
王楷, 梅瑞斌. “人工智能+有限元”模型在轧制领域的研究进展[J]. 材料导报, 2022, 36(13): 20110127-12.
WANG Kai, MEI Reibin. On the Research and Application of “Artificial Intelligence Plus Finite Element” Models in the Field of Rolling. Materials Reports, 2022, 36(13): 20110127-12.
链接本文:  
http://www.mater-rep.com/CN/10.11896/cldb.20110127  或          http://www.mater-rep.com/CN/Y2022/V36/I13/20110127
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