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基于局部约束的不锈钢菱形花纹高度轧制控制策略研究

Research on Control Strategy of Stainless Steel Diamond Plate Pattern Height Rolling Based on Local Constraints.

作者信息

Xin Zezhou, Qiu Siyuan, Wang Chunliu, Qiu Huadong, Sun Chuanmeng, Wu Zhibo

机构信息

School of Electrical and Control Engineering, North University of China, Taiyuan 030051, China.

Olin College, Northeast Forestry University, Harbin 150040, China.

出版信息

Materials (Basel). 2025 Mar 1;18(5):1116. doi: 10.3390/ma18051116.

DOI:10.3390/ma18051116
PMID:40077341
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11901657/
Abstract

The rolling system for stainless steel, particularly in the production of diamond plates, represents a complex industrial control scenario. The process requires precise load distribution to effectively manage pattern height, due to the high strength, hardness, and required dimensional accuracy of the material. This paper addresses the limitations of offline methods, which include heavy reliance on initial conditions, intricate parameter settings, susceptibility to local optima, and suboptimal performance under stringent constraints. A Multi-Objective Adaptive Rolling Iteration method that incorporates local constraints (MOARI-LC) is proposed. The MOARI-LC method simplifies the complex multi-dimensional nonlinear constrained optimization problem of load distribution, into a one-dimensional multi-stage optimization problem without explicit constraints. This simplification is achieved through a single variable cycle iteration involving reduction rate and rolling equipment selection. The rolling results of HBD-SUS304 show that the pattern height to thickness ratio obtained by MOARI-LC is 0.20-0.22, which is within a specific range of dimensional accuracy. It outperforms the other two existing methods, FCRA-NC and DCRA-GC, with results of 0.190.24 and 0.150.25, respectively. MOARI-LC has increased the qualification rate of test products by more than 25%, and it has also been applied to the other six industrial production experiments. The results show that MOARI-LC can control the absolute value of the rolling force prediction error of the downstream stands of the hot strip finishing rolls within 5%, and the absolute value of the finished stand within 3%. These results validate the scalability and accuracy of MOARI-LC.

摘要

不锈钢轧制系统,尤其是在菱形花纹板生产中,代表了一种复杂的工业控制场景。由于材料的高强度、硬度以及所需的尺寸精度,该工艺需要精确的负载分布来有效管理花纹高度。本文探讨了离线方法的局限性,包括对初始条件的严重依赖、复杂的参数设置、易陷入局部最优以及在严格约束下的次优性能。提出了一种纳入局部约束的多目标自适应轧制迭代方法(MOARI-LC)。MOARI-LC方法将负载分布的复杂多维非线性约束优化问题简化为无显式约束的一维多阶段优化问题。这种简化通过涉及压下率和轧制设备选择的单变量循环迭代实现。HBD-SUS304的轧制结果表明,MOARI-LC获得的花纹高度与厚度比为0.20 - 0.22,处于特定的尺寸精度范围内。它优于其他两种现有方法,即FCRA-NC和DCRA-GC,其结果分别为0.190.24和0.150.25。MOARI-LC使测试产品的合格率提高了25%以上,并且还应用于其他六个工业生产实验。结果表明,MOARI-LC可将热轧精轧机下游机架轧制力预测误差的绝对值控制在5%以内,成品机架的绝对值控制在3%以内。这些结果验证了MOARI-LC的可扩展性和准确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d7a/11901657/1246d6dfdbde/materials-18-01116-g014.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d7a/11901657/f2c986a8d7aa/materials-18-01116-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d7a/11901657/70a2d3b211ac/materials-18-01116-g010.jpg
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本文引用的文献

1
Pareto multi-objective optimization of tandem cold rolling settings for reductions and inter stand tensions using NSGA-II.基于NSGA-II的用于压下量和机架间张力的串联冷轧设置的帕累托多目标优化
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