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Alternative TitleMonitoring based on improved OFA-MPCA
边福强; 高翔; 苑明哲
Source Publication中国科学院研究生院学报
Indexed ByCSCD
Contribution Rank2
Funding Organization国家高技术研究发展计划(863计划)(2006AA04Z185);;辽宁省教育厅项目(2005320)资助
Keyword正交函数近似 多向主元分析 间歇过程 Pensim
Other AbstractMultiway Principal Component Analysis (MPCA) is a multivariable statistical approach,which can extract several principal components from the numerous of data to express the data information well,and is mainly used in batch process. In practice,for many reasons,the runtime of each batch is different from others so that the effective statistical model can not be built directly. Orthonormal Function Approximation (OFA) is a technique of project transformation based on orthonormal base,after OFA we can use the projection coefficient to express the characteristics of the original data and synchronize the trajectories of each historical batch and reduce the dimension. This paper presents some improvement on the OFA and combined the MPCA to model and monitor the typical batch process——Penicillin fermentation process. The simulation results show that the improved OFA can deal with data more quickly and the improved OFA-MPCA is able to synchronize the trajectories of all the batches,and monitor the batches perfectly.
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Document Type期刊论文
Corresponding Author边福强
Recommended Citation
GB/T 7714
边福强,高翔,苑明哲. 基于改进的OFA-MPCA的监控方法[J]. 中国科学院研究生院学报,2009,26(2):209-214.
APA 边福强,高翔,&苑明哲.(2009).基于改进的OFA-MPCA的监控方法.中国科学院研究生院学报,26(2),209-214.
MLA 边福强,et al."基于改进的OFA-MPCA的监控方法".中国科学院研究生院学报 26.2(2009):209-214.
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