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|Title:||Nonlinear process monitoring using JITL-PCA|
Principal component analysis
|Citation:||Cheng, C., Chiu, M.-S. (2005-03-28). Nonlinear process monitoring using JITL-PCA. Chemometrics and Intelligent Laboratory Systems 76 (1) : 1-13. ScholarBank@NUS Repository. https://doi.org/10.1016/j.chemolab.2004.08.003|
|Abstract:||A new method is proposed for monitoring the nonlinear static or dynamic systems. In the proposed method, just-in-time learning (JITL) and principal component analysis (PCA) are integrated to construct JITL-PCA monitoring scheme, where JITL serves as the process model to account for the nonlinear and dynamic behavior of the process under normal operating conditions. The residuals resulting from the difference between JITL's predicted outputs and process outputs are analyzed by PCA to evaluate the status of the current process operating condition. Two nonlinear systems are used to illustrate the proposed method. Simulation results show that JITL-PCA outperforms both PCA and dynamic PCA in the monitoring of nonlinear static or dynamic systems. © 2004 Elsevier B.V. All rights reserved.|
|Source Title:||Chemometrics and Intelligent Laboratory Systems|
|Appears in Collections:||Staff Publications|
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