Multi-Objective Optimization of Low-Alloy Hot-Rolled Strip Cooling Process Based on Gray Correlation Analysis

被引:0
|
作者
Xue, Rundong [1 ]
Fei, Aigeng [2 ]
机构
[1] Univ Sci & Technol Beijing, Inst Adv Mat & Technol, Beijing 100083, Peoples R China
[2] Univ Sci & Technol Beijing, Sch Mat Sci & Engn, Beijing 100083, Peoples R China
关键词
hot-rolled strip; residual stress; cooling process; gray correlation analysis; multi-objective optimization; PROCESS-PARAMETERS; RESIDUAL-STRESSES; PREDICTION;
D O I
10.3390/met14020246
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The residual stress in low-alloy hot-rolled strips seriously affects the use and processing of products. Reducing residual stress is important for improving the product quality of hot-rolled strips. In this paper, the changes in grain size and residual stress of hot-rolled strips under different cooling processes were investigated via thermal simulation experiments and electron backscatter diffraction. It was found that the optimum cooling process solution for single-objective optimization of grain size was a final rolling temperature of 875 degrees C, a laminar cooling speed of 50 degrees C/s, and a coiling temperature of 550 degrees C. When single-objective optimization of residual stress was carried out, the optimal cooling process scheme was 900 degrees C for final rolling temperature, 20 degrees C/s for laminar cooling speed, and 625 degrees C for coiling temperature. The significance of the effect of cooling processes on grain size and residual stress was analyzed based on the extreme deviation of the effect of each cooling process on grain size and residual stress in orthogonal experiments. The results show that the coiling temperature was the most influential factor on grain size and residual stress among the cooling process parameters. The difference was that grain size increased with increasing coiling temperature, and residual stress decreased with increasing coiling temperature. Using both grain size and residual stress as evaluation indicators, a multi-objective optimization of the cooling process for hot-rolled strips was carried out via the gray correlation analysis method. The optimized solution was 875 degrees C final rolling temperature, 30 degrees C/s laminar cooling speed, and 625 degrees C coiling temperature. At this time, the grain size was 4.8 mu m, and the KAM (Kernel Average Misorientation) was 0.40 degrees. The grain size under the actual production process scheme was 4.4 mu m with a KAM of 0.78 degrees. Compared to the actual production process solution, the multi-objective optimization solution showed little change in grain size, with only a 9% increase and a 49% reduction in KAM. The optimization scheme in this paper could significantly reduce the level of residual stresses while ensuring the fine grain size of hot-rolled strips, thus improving the overall quality of hot-rolled strips.
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页数:14
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