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Optimization of Roll Shifting Strategy of Alternately Rolling in Hot Strip Mill

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文摘 An optimization solution to roll shifting strategy for alternately rolling campaign is presented. All the strips in a rolling campaign are divided into narrow strips and wide ones, and shifting position of narrow strips is obtained by the recursive method, and then shifting position of wide strips is optimized by NSGA-II which is a multi-objective genetic algorithm. For wide strips, a multi-objective optimization model of roll shifting strategy is proposed, which takes 3 wear contour factors including edge smoothness, body smoothness and edge drop as optimization objectives. The Pareto optimal front of roll shifting strategy can be gained quickly by NSGA-II, which suggests a series of alternative solutions to roll shifting strategy. Analysis shows that the conflict exists among the 3 objectives. The final optimal solution is selected from the Pareto optimal solutions by the weighted-sum decision-making method. Industrial production proves the validity of the solution, and it can improve strip profile of alternately rolling, reduce strip edge wave, and extend the rolling miles of rolling campaigns.
来源 Journal of Iron and Steel Research , International,2012,19(5):37-42 【核心库】
DOI 10.1016/s1006-706x(12)60097-1
关键词 hot strip mill ; alternately rolling ; work roll shifting ; NSGA-II ; pareto optimal solution
地址

1. College of Information Science and Engineering, Northeastern University, Liaoning, Shenyang, 110819  

2. Institute of Automation, Baosteel Technology Center, Shanghai, 201900  

3. Research Institute of Science and Technology, Northeastern University, Liaoning, Shenyang, 110819

语种 英文
文献类型 研究性论文
ISSN 1006-706X
学科 金属学与金属工艺
基金 国家自然科学基金
文献收藏号 CSCD:4538852

参考文献 共 9 共1页

1.  Zhang Qingdong. Shape Control in Schedule Free Hot Strip Rolling. Iron and Steel (in Chinese),2001,36(2):72 被引 1    
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8.  Srinivas N. Multi-Objective Optimization Using Non-Dominated Sorting in Genetic Algorithms. Evolutionary Computation,1994,2(3):221 被引 513    
9.  Kalyanmoy Deb. A Fast Multi-Objective Genetic Algorithms:NSGA-II. IEEE Transaction on Evolutionary Computation,2002,6(2):182 被引 3015    
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