4.5 Article

Design Optimization of Chute Structure Based on E-SVR Surrogate Model

期刊

METALS
卷 13, 期 3, 页码 -

出版社

MDPI
DOI: 10.3390/met13030635

关键词

chute; support vector regression; kernel function; surrogate model; ensemble of surrogates; design optimization

向作者/读者索取更多资源

In this paper, a structure parameter optimization model was established to reduce the wear and damage of the chute caused by long-term impact of coke. The ensemble of support vector regression (E-SVR) with different kernel functions was developed to replace the implicit relationship between the conveying speed, impact force, and structure parameters. Numerical examples were used to verify the effectiveness of the E-SVR model. After optimization, the maximum impact force was reduced by 17.07% and the maximum conveying speed was reduced by 6.59%, which still falls within the specified range. Therefore, the feasibility of the optimization results and the effectiveness of the E-SVR surrogate model were verified.
To reduce the wear and damage of the chute caused by long-term impact of coke, a structure parameter optimization model was established in this paper, which takes the minimum impact force as the objective and the coke-conveying speed as the constraint. Furthermore, the ensemble of support vector regression (E-SVR) with different kernel functions was developed to replace the implicit relationship between the conveying speed, the impact force, and the structure parameters. Using the numerical examples, the effectiveness of the E-SVR model was verified. Finally, the optimal chute structure parameters were obtained by using the E-SVR model. After optimization, the maximum impact force was reduced by 17.07% and the maximum conveying speed was reduced by 6.59%, which still falls within the specified range. Therefore, the feasibility of the optimization results and the effectiveness of the E-SVR surrogate model were verified.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据