최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기Journal of the Taiwan Institute of Chemical Engineers, v.41 no.4, 2010년, pp.475 - 481
Jeng, J.C. (Department of Chemical Engineering and Biotechnology, National Taipei University of Technology, Taipei 106, Taiwan)
In process monitoring, principal component analysis (PCA) is a very popular method and has found wide applications. Conventionally, a fixed PCA model is used for monitoring. This paper presents the use of both recursive PCA (RPCA) and moving window PCA (MWPCA) to online update the PCA model and its ...
IEEE Trans. Signal Process. Champagne 42 2758 1994 10.1109/78.324741 Adaptive Eigendecomposition of Data Covariance Matrices Based on First-order Perturbations
Ind. Eng. Chem. Res. Choi 45 3108 2006 10.1021/ie050391w Adaptive Multivariate Statistical Process Control for Monitoring Time-Varying Processes
EURASIP J. Appl. Signal Process. Erdogus 12 2034 2004 10.1155/S1110865704404120 Recursive Principal Components Analysis Using Eigenvector Matrix Perturbation
Ind. Eng. Chem. Res. He 47 419 2008 10.1021/ie070712z Variable MWPCA for Adaptive Process Monitoring
Jackson 1991 A User's Guide to Principal Components
Technometrics Jackson 21 341 1979 10.2307/1267757 Control Procedures for Residuals Associated with Principal Component Analysis
Ind. Eng. Chem. Res. Jin 45 696 2006 10.1021/ie050850t Robust Recursive Principal Component Analysis Modeling for Adaptive Monitoring
Chemom. Intell. Lab. Syst. Kourti 28 3 1995 10.1016/0169-7439(95)80036-9 Process Analysis, Monitoring and Diagnosis Using Multivariate Projection Methods
J. Process Control Li 10 471 2000 10.1016/S0959-1524(00)00022-6 Recursive PCA for Adaptive Process Monitoring
Chemom. Intell. Lab. Syst. Liu 96 132 2009 10.1016/j.chemolab.2009.01.002 Moving Window Kernel PCA for Adaptive Monitoring of Nonlinear Processes
Control Eng. Pract. MacGregor 3 403 1995 10.1016/0967-0661(95)00014-L Statistical Process Control of Multivariate Process
Malinowski 1991 Factor Analysis in Chemistry
Technometrics Nomikos 37 41 1995 10.2307/1269152 Multivariate SPC Charts for Monitoring Batch Processes
Chemom. Intell. Lab. Syst. Raich 30 37 1995 10.1016/0169-7439(95)00035-6 Multivariate Statistical Methods for Monitoring Continuous Processes: Assessment of Discrimination Power of Disturbance Models Diagnosis of Multiple Disturbances
Ind. Eng. Chem. Res. Wang 44 5691 2005 10.1021/ie048873f Process Monitoring Approach Using Fast Moving Window PCA
J. Process Control Wise 6 329 1996 10.1016/0959-1524(96)00009-1 The Process Chemometrics Approach to Process Monitoring and Fault Detection
Chemom. Intell. Lab. Syst. Wold 23 149 1994 10.1016/0169-7439(93)E0075-F Exponentially Weighted Moving Principal Component Analysis and Project to Latent Structures
J. Process Control Yoon 11 387 2001 10.1016/S0959-1524(00)00008-1 Fault Diagnosis with Multivariate Statistical Models Part I: Using Steady State Fault Signatures
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.