煉鋼–連鑄區段3種典型工序界面技術研究進展

楊建平; 張江山; 劉青

doi:10.13374/j.issn2095-9389.2020.05.08.001

煉鋼–連鑄區段3種典型工序界面技術研究進展

doi: 10.13374/j.issn2095-9389.2020.05.08.001

楊建平¹,
張江山¹,
劉青^{1, 2, ,}

1.
北京科技大學鋼鐵冶金新技術國家重點實驗室，北京 100083
2.
北京科技大學鋼鐵生產制造執行系統教育部工程研究中心，北京 100083

基金項目: 國家自然科學基金資助項目（50874014）；中央高校基本科研業務費資助項目（FRF-BR-17-029A）

詳細信息

通訊作者:
E-mail: qliu@ustb.edu.cn

中圖分類號: TF758
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出版歷程
- 收稿日期: 2020-05-08
- 刊出日期: 2020-12-25

Research progress on three kinds of classic process interface technologies in steelmaking-continuous casting section

1.
State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, Beijing 100083, China
2.
Engineering Research Center of MES Technology for Iron & Steel Production, University of Science and Technology Beijing, Beijing 100083, China

More Information

Corresponding author: E-mail: qliu@ustb.edu.cn

摘要

摘要: 面對鋼廠智能化發展的時代要求，煉鋼–連鑄區段工序界面技術受到越來越多冶金學者的關注，其不僅是解決工序關系集合協同–優化問題的重要手段，也影響著工序功能集合解析–優化和流程工序集合重構–優化的效果。本文對煉鋼–連鑄區段3種典型工序界面技術，即鋼包運行控制、天車運行控制和生產運行模式優化的研究進展進行闡述，其中，鋼包運行控制包括鋼包熱狀態監測、鋼包選配以及鋼包調度，天車運行控制包括吊運任務的分配和同跨/異跨天車的協同調度，生產運行模式優化包括工序/設備產能、時間節奏與爐–機對應模式的匹配設計。此外，針對煉鋼–連鑄區段多工序協同運行的制約因素，指出工序界面技術協同的必要性，并對上述工序界面技術的協同機制與協同方案進行了闡述。
- 煉鋼–連鑄 /
- 工序界面技術 /
- 鋼包運行 /
- 天車運行 /
- 生產運行模式 /
- 協同
Abstract: Metallurgical process engineering proposed by academician Ruiyu Yin is a new branch in the field of metallurgy, which deals with the physical nature, structure, and global behavior of metallurgical manufacturing process. Process interface technology used in steelmaking-continuous casting section (SCCS) is developed from metallurgical process engineering. It is used to study and analyze the running dynamics of mass flow in steelmaking plants. In recent years, the intelligent and green production in steelmaking plants has become the demand and necessity of the time because of the rapid development of intelligent manufacturing represented by Industry 4.0 in Germany. Nowadays, the automation control of single-process has been realized in most steelmaking plants at home and abroad, which is a stepping zone and has created the foundation for the intelligent and green production. But at the same time, importance also should be given for the improvement in the multi-process operation of SCCS considering the global optimization on steelmaking production. Undoubtedly the process interface technology is an important method to deal with the collaboration-optimization of process relationship set, but also it has a greater influence on the analysis-optimization of process function set and the reconstruction-optimization of process set. Therefore, the process interface technology has created lot of interest and drawn greater attention from scholars and experts of metallurgy, which results in the great improvement of the multi-process operation in SCCS. Currently, three kinds of classic process interface technologies, including ladle cycling control, crane running control, and operation mode optimization, have become the most important research areas because of their significant effect on the high-efficient connection of mass flow among multi-process. The scope of ladle cycling control includes the monitoring of thermal state and the matching and scheduling of ladles. The task assignment and multi-crane collaborative scheduling are the most important components of crane running control and it is of great interest to research further. When operation mode optimization is considered, the improvement of furnace-caster coordinating mode based on the matching of capacity and rhythm can be regarded as the most interesting research area. It is known that the operation mode is the fundamental for ladle cycling and crane running, and moreover, the status of ladle cycling and crane running also can guide the further optimization of operation mode. Based on above analysis, this paper presented a detailed overview of progress made in the research on abovementioned three kinds of classic process interface technologies in SCCS. Further, the necessity of collaboration between process interface technologies was also illustrated, aiming at unfavorable restraints of multi-process collaborative operation. In addition, the collaboration mechanisms and schemes of all three kinds of classic process interface technologies were described in detail. Finally, it is expected that this review could offer some reference and guidance for the improvements in multi-process operation of SCCS.
- steelmaking-continuous casting /
- process interface technology /
- ladle cycling /
- crane running /
- operation mode /
- collaboration

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圖 1 煉鋼?連鑄區段鋼包運行示意圖

Figure 1. Schematic of ladle cycling in SCCS

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圖 2 鋼包包殼溫度與熱流量分布圖^[18]。（a）溫度分布；（b）熱流量分布

Figure 2. Distributions of temperature and heat ?ux on ladle shell^[18]: (a) temperature distribution; (b) heat flux distribution

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圖 3 鋼包調度示意圖

Figure 3. Schematic of ladle scheduling

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圖 4 鋼包運行管控系統技術架構圖

Figure 4. Technical framework of the control system for ladles cycling

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圖 5 國內某鋼廠車間布置和天車配置

Figure 5. Workshop layout and crane configuration in steelmaking plant

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圖 6 生產模式在鋼廠系統中的地位及其邏輯關系^[70]

Figure 6. Status of operation mode in steelmaking plant system^[70]

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圖 7 “層流”運行模式

Figure 7. “Laminar flow” operation mode

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圖 8 模型應用前后爐–機對應關系^[75]。（a）應用前；（b）應用后

Figure 8. Furnace?caster coordinating scenario^[75]: (a) before application; (b) after application

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圖 9 鋼包、天車運行控制與生產運行模式優化的協同機制

Figure 9. Collaboration mechanism among ladle cycling control, crane running control, and operation mode optimization

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表 1 鋼包熱狀態影響因素的研究

Table 1. Study on influence factors on thermal state of ladles

No.	Authors (Year)	Influencing factors	Methods (tools)/Model types	Refs.
1	Xia (2001)	Initial temperature of ladle lining, heat dissipation rate of slag layer, and bottom blowing or not	CFX software/Two dimensional heat transfer model	[22-23]
2	Volkova (2003)	Lining thickness and working layer materials	Two dimensional heat transfer model	[24]
3	Bj?rn (2011)	Lining thickness, distance from cover to ladle edge, and preheating time	COMSOL software/Two dimensional heat transfer model	[25]
4	Tripathi (2012)	Thickness of slag layer, tapping temperature, ladle life, and initial temperature of ladle lining	Software of Gambit and Fluent/Two dimensional heat transfer model	[26]
5	Huang (2016)	Repair time, preheating time, baking gas temperature, and cooling time	Two dimensional heat transfer model	[27]
6	Phanomchoeng (2016)	Thermal resistance for different materials and thermal resistance for the same material with different temperatures	Bounded Jacobian nonlinear observer/One dimensional heat transfer model	[28]
7	Gong (2016)	Online/offline preheating time, cooling time, and erosion degree of ladle lining	Ansys software with ParaMesh/Two dimensional heat transfer model	[29]
8	Wang (2017)	Materials and structures of ladle lining	Fluent software/Three dimensional heat transfer model	[30]
9	Yuan (2018)	Ladle preheating methods	Fluent software/Three dimensional heat transfer model	[31]
10	Santos (2018)	Working layer materials and insulation layer or not	Abaqus software/Two dimensional heat transfer model	[32]
11	Hou (2018)	Thickness and thermal conductivity of ladle lining	Abaqus software and Taguchi approaches/Two dimensional heat transfer model	[33]

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表 2 近年來關于天車調度的代表性研究工作

Table 2. Study on crane scheduling in recent years

No.	Authors (Year)	Modeling methods	Solving methods	Characteristics	Refs.
1	Xu (2007)	Cellular automata	Heuristic and genetic algorithms	Verify the feasibility of results through cellular automata	[55]
2	Ma (2010)	Multi-agent	Heuristic algorithm	Improve the reliability of results by frequent interaction among different agents and parallel computing strategy	[56]
3	Liu (2011)	Mathematical programming	Heuristic algorithm	Coordinated scheduling between ladles and cranes	[57]
4	Sun (2011)	Mixed-timed Petri Net	Branch-and-cutmethod	Transform crane scheduling problem into the linear model	[58]
5	Xie (2012)	Mathematical programming	Variable neighborhood search algorithm	Optimize algorithm parameters by artificial neural network	[59]
6	Yu (2012)	Mathematical programming	Genetic and heuristic algorithms	Solve the static and dynamic crane scheduling models respectively by genetic and heuristic algorithms	[60]
7	Zhu (2013)	Petri Net with UML	Heuristic algorithm	Make up the deficiency of UML on formal expression by Petri Net	[61]
8	Zheng (2013)	Mathematical programming	Immune genetic algorithm	Prominent local search ability of the algorithm and strong global diversity of solutions	[62]
9	Wang (2014)	Mathematical programming	Improved Memetic algorithm	Design decoding operator based on task allocation and conflicts eliminating rules	[63]
10	Jiang (2016)	Mathematical programming	Improved genetic algorithm	Design encoding operator based on matrix form, and solve task priority and crane selection in parallel	[64]
11	Gao (2017)	Mathematical programming	Improved genetic algorithm	Minimize the total transfer times of tasks and balance the task allocations among cranes	[65]
12	Li (2019)	Mathematical programming	Heuristic algorithm	Apply the predictive reactive rescheduling strategy	[66]
13	Pang (2019)	Mathematical programming	Heuristic algorithm	Apply analytical hierarchy process (AHP) fuzzy comprehensive evaluation to analyze crane scheduling	[67]
14	Yang (2019)	Plant simulation	Heuristic algorithm	Coordinated scheduling among ladles, cranes, and heat plans	[68]

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