Determining the number of principal components for best reconstruction

Journal of Process Control

Volumn 10, Issue 2, 2000, Pages 245-250

  Qin, S Joe ^a   Dunia, Ricardo ^a  

^a The University of Texas at Austin   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CORRELATION METHODS; ERROR ANALYSIS; MATHEMATICAL MODELS; SENSORS;

PRINCIPAL COMPONENT ANALYSIS (PCA) MODELS; VARIANCE OF RECONSTRUCTION ERROR (VRE);

PROCESS CONTROL;

EID: 0033903077     PISSN: 09591524     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0959-1524(99)00043-8     Document Type: Article

References (15)

1. Nomikos P., MacGregor J.F. Multivariate SPC charts for monitoring batch processes. Technometrics. 37 (1):1995;41-59.
2. MacGregor J.F., Koutodi M. Statistical process control of multivariate processes. Control Engineering Practice. 3:1995;403-414.
3. Harmon J.L., Duboc P.H., Bonvin D. Factor analytical modeing of biochemical data. Comput. Chem. 19:1995;1287-1300.
4. M. Piovoso, K. Kosanovich, R. Pearson, Monitoring process performance in real time, in: Proceedings of ACC, Chicago, 1992, pp. 2359-2363.
5. Martens H., Naes T. Multivariative Calibration. 1989;John Wiley and Sons, New York.
6. Wise, B.M., Ricker, N.L. Recent advances in multivariative statistical process control: Improving robustness and sensitivity, in: Proceedings of the IFAC. ADCHEM Syposium, 1994, 125-130.
7. Dunia R., Qin J., Edgar T.F., McAvoy T.J. Identification of faulty sensors using principal component analysis. AIChE J. 42:1996;2797-2812.
8. R. Dunia, S.J. Qin, A unified geometric approach to process and sensor fault identification, Comput. Chem. In press.
9. Ku W., Storer R.H., Georgakis C. Disturbance detection and isolation by dynamic principal component analysis. Chem. Intell. Lab. Sys. 30:1995;179.
10. Wold S. Cross validatory estimation of the number of components in factor and principal component analysis. Technometrics. 20:1978;397-406.
11. Joreskog K., Klovan J., Reyment R. Geological Factor Analysis. 1976;Elsevier, Amsterdam.
12. Cattell R.B. Multivariate Behav. Res. 1:1996;245.
13. Malinowski E.R. Factor Analysis in Chemistry. 1991;Wiley-Interscience, New York.
14. Wold S., Esbensen K., Geladi P. Principal component analysis. Chemometrics and Intelligent Laboratory Systems. 2:1987;37-52.
15. Valle-Cervantes, S., Li, W., Qin, S.J. Determining the number of principal components, in: AIChE Annual Meeting, paper 224h, 15-20 November 1998, Miami, FL.