王普,曹彩霞,高学金,常鹏,齐咏生

• 1:北京工业大学信息学部
• 2:数字社区教育部工程研究中心
• 3:城市轨道交通北京实验室
• 4:计算智能与智能系统北京市重点实验室

摘要(Abstract)：

为考虑质量变量对阶段划分结果的影响,提高建模精度,提出了一种基于扩展得分矩阵的多阶段间歇过程质量预测方法。首先将三维过程数据沿批次方向展开为二维数据矩阵,对每个时间片矩阵进行偏最小二乘(partial least squares,PLS)分析得到可以表征过程变量的得分矩阵和可以表征质量变量的得分矩阵;然后构建每个时间片的扩展得分矩阵,利用扩展得分矩阵捕捉质量变量信息对划分阶段的影响,采用CS (Cauchy-Schwarz)统计量计算相邻两个扩展得分矩阵的相似度,依据相似度将操作过程划分为不同的操作阶段,对划分后的各个阶段分别建立MPLS质量预测模型;最后将该算法在青霉素发酵仿真实验平台和大肠杆菌生产数据上进行了实验验证,实验结果表明了本文所提方法的可行性和有效性。

关键词(KeyWords)： 多阶段;扩展得分矩阵;CS统计量;质量预测

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金(61640312,61763037);; 北京市自然科学基金(4172007);; 北京市教育委员会资助

作者(Author): 王普,曹彩霞,高学金,常鹏,齐咏生

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