| 引用本文: | 陈聪,吴敏,陈略峰,章文,杜胜.基于工况识别的辊式淬火过程板形预报方法[J].控制理论与应用,2021,38(9):1407~1413.[点击复制] |
| CHEN Cong,WU Min,CHEN Lue-feng,ZHANG Wen,DU Sheng.Flatness prediction method based on operating mode recognition for roller quenching process[J].Control Theory and Technology,2021,38(9):1407~1413.[点击复制] |
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| 基于工况识别的辊式淬火过程板形预报方法 |
| Flatness prediction method based on operating mode recognition for roller quenching process |
| 摘要点击 1652 全文点击 635 投稿时间：2020-09-17 修订日期：2021-08-13 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| DOI编号 10.7641/CTA.2021.00626 |
| 2021,38(9):1407-1413 |
| 中文关键词 辊式淬火 板形预报 工况识别 支持向量机 粒子群优化算法 |
| 英文关键词 roller quenching flatness prediction operating mode recognition support vector machine particle swarm optimization algorithm |
| 基金项目 湖北省自然科学基金创新群体项目(2015CFA010), 高等学校学科创新引智计划项目(B17040) |
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| 中文摘要 |
| 板形是衡量淬火后钢板质量的重要指标之一, 板形的预报对高质量钢板的持续稳定生产具有重要的指导
意义. 本文提出一种基于工况识别的辊式淬火过程板形预报方法, 为淬火生产控制决策提供参考依据. 首先对淬火
过程进行特性分析; 然后采用模糊C均值聚类算法对淬火过程进行工况识别, 使用支持向量机建立各工况的板形预
报模型, 并运用改进的粒子群优化算法提高模型的精度; 最后利用工业生产数据进行实验, 结果验证了本文所提方
法的可行性与有效性. |
| 英文摘要 |
| Flatness is an important indicator to measure the quality of quenched steel plate, and the prediction of flatness
is of great significance for the continuous and stable production of high-quality steel plate. This paper proposes a method
based on operating mode recognition to predict the flatness for the roller quenching process, which provides a reference
for the quenching production control decision. Firstly, the characteristics of the quenching process are analyzed. Then the
fuzzy C-means clustering algorithm is used to recognize the operating modes of the process, the support vector machine
is used to establish the flatness prediction model for each operating mode, and the improved particle swarm optimization
algorithm is applied to improve the accuracy of the model. Finally, experiments are performed using industrial production
data, and the results verify the feasibility and effectiveness of the flatness prediction method proposed in this paper. |
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