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提高双层铸轧辊的使用寿命及评估XGBoost机器学习方法在其质量控制中的适用性

Increasing Exploitation Durability of Two-Layer Cast Mill Rolls and Assessment of the Applicability of the XGBoost Machine Learning Method to Manage Their Quality.

作者信息

Vlasenko Tetiana, Glowacki Szymon, Vlasovets Vitaliy, Hutsol Taras, Nurek Tomasz, Lyktei Viktoriia, Efremenko Vasily, Khrunyk Yuliya

机构信息

Department of Management, Business and Administration, State Biotechnology University, Alchevsky St., 44, 61002 Kharkiv, Ukraine.

Department of Fundamentals of Engineering and Power Engineering, Institute of Mechanical Engineering, Warsaw University of Life Sciences (SGGW), 02-787 Warsaw, Poland.

出版信息

Materials (Basel). 2024 Jul 1;17(13):3231. doi: 10.3390/ma17133231.

DOI:10.3390/ma17133231
PMID:38998314
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11242610/
Abstract

The increase in exploitation durability of two-layer cast rolls with the working layer made of high chromium cast iron allows one to significantly improve the quality of rolled metal as well as to increase the economic efficiency of the manufacturing process. However, it is severely hindered due to the massiveness of castings, the impossibility of both evaluating mechanical properties along the depth of the working layer, and providing the structural uniformity of the working surface and the decrease in stresses. In our research, aiming to enhance the exploitation durability of sheet rolls, it is recommended to achieve structural uniformity by CuMg alloying, which increases the concentration of copper up to 2.78 wt.% in certain zones and, owing to the accelerated austenite decomposition at a high temperature during the cool-down of the castings, led to the reduction in excessive strength and the level of heat stresses in the castings. We propose the regimes of cyclic heat treatments which, due to the decomposition of retained austenite and the fragmentation of structure, control the level of hardness to reduce and uniformize the level of stresses along the length of a barrel. A further improvement in the predictions of exploitation durability using XGboost method, which was performed based on the chemical composition of the working layer of high-chromium cast iron and heat treatment parameters, requires taking into account the factors characterizing exploitation conditions of specific rolling mills and the transformations of structural-phase state of the surface obtained by a non-destructive control method. As the controlled parameter, the hardness measured on the roll's surface is recommended, while the gradient change in mechanical properties along the working layer depth can be feasibly analyzed by a magnetic method of coercive force measuring.

摘要

工作层由高铬铸铁制成的双层铸轧辊,其使用耐久性的提高使得轧制金属的质量显著提升,同时制造过程的经济效率也得以提高。然而,由于铸件的厚重性,无法沿工作层深度评估机械性能,也难以保证工作表面的结构均匀性以及应力的降低,这严重阻碍了其发展。在我们的研究中,为提高薄板轧辊的使用耐久性,建议通过铜镁合金化实现结构均匀性,这会使某些区域的铜浓度增加至2.78 wt.%,并且由于铸件冷却过程中高温下奥氏体的加速分解,导致铸件中的过度强度和热应力水平降低。我们提出了循环热处理制度,由于残余奥氏体的分解和组织的破碎,该制度可控制硬度水平,以降低并使沿辊身长度的应力水平均匀化。使用XGboost方法基于高铬铸铁工作层的化学成分和热处理参数对使用耐久性进行预测的进一步改进,需要考虑表征特定轧机使用条件的因素以及通过无损控制方法获得的表面结构相状态的转变。作为控制参数,建议测量轧辊表面的硬度,而沿工作层深度的机械性能梯度变化可通过测量矫顽力的磁性方法进行可行分析。

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