Research on Mechanical Performance Testing and Influencing Factors of Strip Steel Products

针对冷轧带钢加工工序中各阶段的工艺参数之间存在耦合性,难以建立该工序的机理模型,难以对在线的产品质量进行合理控制与优化等问题。文章通过相关性分析法确定了对带钢硬度具有重要影响的参数,并使用主成分分析法建立了一个数据驱动的带钢产品质量检测模型,并用最小二乘估计法进行拟合。结果表明:可以有效地确定影响带钢硬度的性能参数,并在此基础上建立一个可以帮助工作人员的质量检测模型。In response to the coupling between process parameters in each stage of the cold-rolled strip processing process, it is difficult to establish a mechanism model for this process and to reasonably control and optimize the quality of online products. The article determined the parameters that have a significant impact on the hardness of strip steel through correlation analysis, and established a data-driven quality inspection model for strip steel products using principal component analysis. The model was fitted using the least squares estimation method. The results indicate that the performance parameters affecting the hardness of the strip steel can be effectively determined, and a quality inspection model that can assist workers can be established based on this.

Authors

Publication Details

Journal
Modeling and Simulation
Published
2025-01-01
DOI
https://doi.org/10.12677/mos.2025.144292
Citations
1
Primary Topic
Metallurgy and Material Forming
Type
article
Field-Weighted Citation Impact
0.86
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article

Research on Mechanical Performance Testing and Influencing Factors of Strip Steel Products

宇鑫 才
1 citations
Modeling and Simulation
Metallurgy and Material Forming
0.86
article

Research on Mechanical Performance Testing and Influencing Factors of Strip Steel Products

宇鑫 才
article en
1 citations

Abstract

针对冷轧带钢加工工序中各阶段的工艺参数之间存在耦合性,难以建立该工序的机理模型,难以对在线的产品质量进行合理控制与优化等问题。文章通过相关性分析法确定了对带钢硬度具有重要影响的参数,并使用主成分分析法建立了一个数据驱动的带钢产品质量检测模型,并用最小二乘估计法进行拟合。结果表明:可以有效地确定影响带钢硬度的性能参数,并在此基础上建立一个可以帮助工作人员的质量检测模型。In response to the coupling between process parameters in each stage of the cold-rolled strip processing process, it is difficult to establish a mechanism model for this process and to reasonably control and optimize the quality of online products. The article determined the parameters that have a significant impact on the hardness of strip steel through correlation analysis, and established a data-driven quality inspection model for strip steel products using principal component analysis. The model was fitted using the least squares estimation method. The results indicate that the performance parameters affecting the hardness of the strip steel can be effectively determined, and a quality inspection model that can assist workers can be established based on this.

Modeling and SimulationVol. 14(04)
Openalex Percentile: Top 32%
Metallurgy and Material Forming
0.86
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