Multivariate statistical process control based on multiway locality preserving projections

作者：Hu, Kunlun; Yuan, Jingqi^*

来源：Journal of Process Control, 2008, 18(7-8): 797-807.

DOI：10.1016/j.jprocont.2007.11.002

• locality preserving projections
• multivariate statistical process control
• batch process monitoring
• fault detection and diagnosis
• moving window technique
• robustness

An approach for multivariate statistical process control based on multiway locality preserving projections (LPP) is presented. The recently developed LPP is a linear dimensionality reduction technique for preserving the neighborhood structure of the data seta It is characterized by capturing the intrinsic structure of the observed data and finding more meaningful low-dimensional information hidden in the high-dimensional observations compared with PCA. In this study, LPP is used to extract the intrinsic geometrical structure of the process data. Hotelling's T-2 (D) and the squared prediction error (SPE or Q) statistic charts for on-line monitoring are then presented, and the contribution plots of these two statistical indices are used for fault diagnosis. Moreover, a moving window technique is used for the implementation of on-line monitoring. Case study was carried out with the data of industrial penicillin fed-batch cultivations. As a comparison, the results obtained with the MPCA are also presented. It is concluded that the Multiway LPP (MLPP) outperforms the conventional MPCA. Finally, the robustness of the MLPP monitoring is analyzed by adding noises to the original data.

• 出版日期2008-9
• 单位上海交通大学