Principal component analysis for fault detection and diagnosis. Experience with a pilot plant

International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics - Proceedings

Volumn , Issue , 2010, Pages 147-152

  Villegas, Thamara ^a   Fuente, María Jesús ^b   Rodríguez, Miguel ^a  

^a UNIVERSIDAD SIMÓN BOLÍVAR   (Venezuela)

^b UNIVERSITY OF VALLADOLID   (Spain)

Author keywords

Fault detection; Fault diagnosis; Principal component analysis (PCA)

Indexed keywords

ACTUAL SYSTEM; CLOSED LOOPS; DATA SETS; FAULT DETECTION AND DIAGNOSIS; LINEAR DIMENSIONALITY REDUCTION; NORMAL OPERATIONS; PCA MODEL; PRINCIPAL COMPONENT ANALYSIS (PCA); Q STATISTICS; SYSTEM BEHAVIORS;

ARTIFICIAL INTELLIGENCE; FAULT DETECTION; INTERACTIVE COMPUTER SYSTEMS; MACHINERY; MAN MACHINE SYSTEMS; MATHEMATICAL MODELS; PILOT PLANTS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 79958742967     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. J. Chen and R.J. Patton. Robust Model-Based Diagnosis for Dynamics Systems, Kluber. Academic Publisher; 1999.
2. J.E. Jackson and G.S. Mudholkar, "Control procedures for residuals associated with principal component analysis", Technometrics, vol. 21, 1979, pp. 341-349. (Pubitemid 9472204)
3. T. Kourti, Process Analysis and Abnormal Situation Detection: From Theory to Practice, IEEE Control System Magazine, 2002, pp 10-25. (Pubitemid 35298306)
4. B.M. Wise and N.B. Gallagher, The Process Chemometrics Approach to Process Monitoring and Fault Detection, Journal of Process Control, vol. 6, 1996, pp 329-348. (Pubitemid 126375552)
5. C. Chatfield and A.J. Collins, Introduction to Multivariate Analysis, Chapman and Hall/CRC; 2000.
6. J.F. MacGregor, T. Kourti and P. Nomikos, "Analysis, monitoring and fault diagnosis of industrial processes using multivariate statistical projection methods", In Proceedings of IFAC Congress, vol. M, 1996, pp. 145U″150.
7. A.C. Raich and A. Cinar, "Process disturbance diagnosis by stadistical distance and angle measures", In Proceedings of IFAC Congress, vol. M, 1996, pp. 283U″288.
8. M. A. Kramer, "Nonlinear principal component analysis using autoas-sociative neural networks", AIChE J., vol. 37(2), 1991, pp. 233U″243.
9. D. Dong and T.J. McAvoy, "Nonlinear principal component analysis- Based on Principal Curses and Neural Networks", Computers chem. Engng, vol. 2, 1996, pp. 65-78.
10. A.A. Afifi and V. Clark. Computer-Aided Multivariate Analysis, Third Ed. Chapman-Hall/CRC; 1996.
11. R.B. Castell, "The Scree test for the number of factors", Journal Multivariate Behavioral Research, vol. 1, 1966, pp. 245-276.
12. L.H. Chiang, E.L. Russell and R.D. Braatz. Fault detection and diagnosis in industrial systems. Springer-Verlag; 2001.
13. R.A. Johnson and D.W. Wichern, Applied Multivariate Statistical Analysis. Second Ed. Prentice-Hall; 1998.