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| 基于偏最小二乘回归模型的带钢热镀锌质量监控方法 | |
| 引用本文： | 姚林,阳建宏,徐金梧,王植.基于偏最小二乘回归模型的带钢热镀锌质量监控方法[J].北京科技大学学报,2007,29(6):627-631. |
| 作者姓名： | 姚林 阳建宏 徐金梧 王植 |
| 作者单位： | 1. 北京科技大学机械工程学院,北京,100083;鞍山钢铁集团公司,鞍山,1140213 2. 北京科技大学机械工程学院,北京,100083 3. 鞍钢股份有限公司冷轧厂,鞍山,114030 |
| 摘 要： | 提出了基于偏最小二乘回归模型的带钢热镀锌质量监控方法. 以带钢热镀锌生产中带钢力学性能和锌层质量的质量监控为研究对象,用偏最小二乘方法建立了生产过程参数与质量结果之间的回归模型,对生产过程控制能力进行了分析,并给出了产品质量的预测方法. 用鞍钢股份有限公司带钢热镀锌的实际生产数据进行验证. 结果表明,偏最小二乘法比传统的多元线性回归方法具有更好的预测精度,基于偏最小二乘回归的锌层质量预测模型,其相对预测误差可达到5.93%. |
| 关 键 词： | 带钢热镀锌 偏最小二乘法 质量监控 预测方法 最小 回归模型 带钢热镀锌 质量预测模型 监控方法 least squares regression partial based strip method of monitoring 相对预测误差 锌层 预测精度 多元线性回归方法 乘法 验证 生产数据 有限 股份 |
| 修稿时间： | 2006-10-312007-01-25 |
Quality monitoring method of strip hot-dip galvanizing based on partial least squares regression |
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| YAO Lin,YANG Jianhong,XU Jinwu,WANG Zhi.Quality monitoring method of strip hot-dip galvanizing based on partial least squares regression[J].Journal of University of Science and Technology Beijing,2007,29(6):627-631. | |
| Authors: | YAO Lin YANG Jianhong XU Jinwu WANG Zhi |
| Institution: | 1 Mechanical Engineering School, University of Science and Technology Beijing, Beijing 100083, China; 2 Anshan Iron and Steel Group Corporation, Anshan 114021, China; 3 Cold Rolling Plant, Angang Steel Company Limited, Anshan 114030, China |
| Abstract: | A quality monitoring method for strip hot-dip galvanizing based on partial least square regression was proposed. Taking the quality monitoring of mechanical properties and zinc coating mass in strip hot-dip galvanizing as the investigated subject, a regression model between process parameters and quality results was constructed through partial least square method. With the regression model, the capability of production process control was analyzed and a production quality prediction method was presented, Real field data from strip hot-dip galvanizing production in Angang Steel Company Limited were used for validation, The results show that partial least square regression has a better predicting precision than traditional multiple linear regression, and that the zinc coating mass prediction model based on partial least square regression has a relative prediction error of 5.93%, |
| Keywords: | strip hot-dip galvanizing partial least square quality monitoring prediction method |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |