铝电解生产智能优化制造研究综述

桂卫华; 岳伟超; 谢永芳; 张红亮; 阳春华

doi:10.16383/j.aas.2018.c180198

铝电解生产智能优化制造研究综述

doi: 10.16383/j.aas.2018.c180198 cstr: 32138.14.j.aas.2018.c180198

1.
中南大学信息科学与工程学院长沙 410083
2.
中南大学冶金与环境学院长沙 410083

基金项目:

国家自然科学基金 61751312

国家自然科学基金 61773405

中南大学创新创业师生共创项目 502390003

国家自然科学基金 61621062

国家自然科学基金 61725306

国家自然科学基金 61533020

详细信息

作者简介:
桂卫华中国工程院院士, 中南大学信息科学与工程学院教授.1981年获得中南矿冶学院硕士学位.主要研究方向为工业大系统递阶和分散控制理论及应用, 复杂工业过程建模, 优化与控制应用和知识自动化.E-mail:gwh@csu.edu.cn

岳伟超中南大学博士研究生.2011年获得郑州轻工业大学学士学位.主要研究方向为迭代学习控制, 知识自动化, 知识表示与知识推理, 工业大数据.E-mail:yue_weichao@163.com

张红亮中南大学冶金与环境学院副教授.2002年获得中南大学学士学位.主要研究方向为有色金属反应器的设计, 诊断与工艺优化的电-磁-流-热-应力场的高效工程化仿, 新型仿真算法的开发, 反应器的物理场测试.E-mail:csu13574831278@csu.edu.cn

阳春华中南大学信息科学与工程学院教授.1985年获得中南工业大学学士学位.主要研究方向为复杂工业过程建模与优化, 分析检测与自动化装置, 智能化系统.E-mail:ychh@mail.csu.edu.cn

通讯作者:
谢永芳中南大学信息科学与工程学院教授.1993年获得中南工业大学学士学位.主要研究方向为分散控制和鲁棒控制, 过程控制, 工业大数据和知识自动化.本文通信作者.E-mail:yfxie@mail.csu.edu.cn

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出版历程
- 收稿日期: 2018-04-09
- 录用日期: 2018-09-17
- 刊出日期: 2018-11-20

A Review of Intelligent Optimal Manufacturing for Aluminum Reduction Production

1.
School of Information Science and Engineering, Central South University, Changsha 410083
2.
School of Metallurgy and Environment, Central South University, Changsha 410083

Funds:

National Natural Science Foundation of China 61751312

National Natural Science Foundation of China 61773405

the Innovation Project of Central South University 502390003

National Natural Science Foundation of China 61621062

National Natural Science Foundation of China 61725306

National Natural Science Foundation of China 61533020

More Information

Author Bio:
Academician of the Chinese Academy of Engineering, and professor at the School of Information Science and Engineering, Central South University. He received his master degree from Central South Institute of Mining and Metallurgy in 1981. His research interest covers the theory and application of hierarchical and decentralized control of industrial large systems, complex industrial process modeling, optimization and control applications, and knowledge automation

Ph. D. candidate at Central South University. He received his bachelor degree from Zheng- zhou University of Light Industry in 2011. His research interest covers iterative learning control, knowledge automation, knowledge representation and knowledge reasoning, and industrial big data

Associate professor at the School of Metallurgy and Environment, Central South University. He received his bachelor degree from Central South University in 2002. His research interest covers non-ferrous metal reactor design, high efficiency engineering simulation of electromagnetic-fluid-thermal-stress field for diagnosis and process optimization, development of new simulation algorithm, and physical field test of reactor

Professor at the School of Information Science and Engineering, Central South University. She received her bachelor degree from Central South University of Technology in 1985. Her research interest covers complex industrial process modeling and optimization, analysis, detection and automation, and intelligent system

Corresponding author: XIE Yong-Fang Professor at the School of Information Science and Engineering, Central South University. He received his bachelor degree from Central South University of Technology in 1993. His research interest covers decentralized control and robust control, process control, industrial big data, and knowledge automation. Corresponding author of this paper

摘要

摘要: 铝电解行业具有战略基础地位，面临着诸多挑战性难题，包括原料来源复杂使得工况难以稳定优化运行、多目标协同优化难度大、控制决策智能化水平和数据利用率低以及铝电解企业在内外环境的不确定性影响下难以实时做出正确决策等.为了解决上述问题，本文提出构建一种集铝电解智能分布式感知系统、系列槽智能协同优化控制系统、大型槽智能优化控制系统、智能安全运行监控系统和虚拟制造系统于一体的铝电解智能优化制造系统的方法.同时提出了铝电解制造系统的未来发展目标和愿景功能，并给出了相关研究方向.最后给出了技术发展规划，提出中短期规划和中长期规划"两步走"战略，并对铝电解生产智能优化制造系统发展前景作出展望.
- 智能优化制造 /
- 铝电解 /
- 挑战与愿景 /
- "两步走"战略
Abstract: The aluminum reduction industry has a strategic foundation position, facing problems such as complex source of raw materials, optimized operating condition, multi-objective collaborative optimization with difficulty, low level of decision-making intelligence and data utilization, and real-time control decision-making under uncertainties in both internal and external environment. In order to solve these problems, the strategy of building an aluminum reduction intelligent optimization manufacturing system is proposed, which includes intelligent distributed sensing system for aluminum reduction, intelligent cooperative optimization control systems of series cells, intelligent optimization control system of large cell, intelligent safety operation monitoring system and virtual manufacturing system. In addition, the future development goals and vision of the manufacturing system are put forward with detailed research targets. At last, a road map of development is given, and the strategy of two steps according to mid-short term plan and mid-long term plan is proposed, and, the prospect of intelligent optimal manufacturing system for aluminum reduction production is presented as well.
- Intelligent optimal manufacturing /
- aluminum reduction /
- challenges and vision /
- "two-step" strategy
注释:

1) 本文责任编委付俊

HTML全文

图 1 铝电解智能优化制造系统

Fig. 1 Aluminum reduction intelligent optimization manufacturing system

下载: 全尺寸图片幻灯片

图 2 铝电解智能优化制造系统技术发展规划

Fig. 2 Development planning of aluminum reduction intelligent manufacturing system

下载: 全尺寸图片幻灯片

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