Multivariate statistical analysis for detection and identification of faulty sensors using latent variable methods

CIMTEC 2008 - Proceedings of the 3rd International Conference on Smart Materials, Structures and Systems - Emboding Intelligence in Structures and Integrated Systems

Volumn 56, Issue , 2008, Pages 501-507

  Hernandez Garcia, Miguel R ^a   Masri, Sami F ^a  

^a University of Southern California ^*  (United States)

Author keywords

Fault detection; Latent variable model; Multivariate statistical analysis; Sensor network

Indexed keywords

DYNAMICAL SYSTEMS; ELECTRON EMISSION; FAULT DETECTION; INTEGRATED CONTROL; INTELLIGENT MATERIALS; MULTIVARIANT ANALYSIS; SENSOR NETWORKS;

DETECTION AND IDENTIFICATIONS; FAULTY SENSOR; LATENT VARIABLE METHODS; LATENT VARIABLE MODELING; MULTI-SENSOR NETWORKS; MULTIVARIATE STATISTICAL ANALYSIS; NETWORK MONITORING;

STATISTICAL METHODS;

EID: 62449329396     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.4028/www.scientific.net/AST.56.501     Document Type: Conference Paper

References (10)

1. L.H. Chiang, E.L. Russell and R.D. Braatz. Fault Detection and Diagnosis in Industrial Systems. Springer-Verlag, London, 2001.
2. R Isermann. Fault-Diagnosis Systems. Springer-Verlag, Berlin, 2006.
3. T. Kourti. Application of latent variable methods to process control and multivariate statistical process control in industry. International Journal of Adaptive Control and Signal Processing, 19:213-246, 2005.
4. S.J. Qin. Statistical process monitoring: basics and beyond. Journal of Chemometrics, 17:480-502, 2003.
5. G. Kerschen, P. De Boe, J.C. Golinval and K. Worden. Sensor validation using principal component analysis. Smart Materials and Structures, 14:36-42, 2005.
6. M. Friswell and D.J. Inman. Sensor validation for smart structures. Journal of Intelligent Material Systems and Structures, 10:973-982, 1999.
7. I.T. Jolliffe. Principal Component Analysis. Springer-Verlag, New York, 2nd edition, 2002.
8. A. Hyvärinen and E. Oja. Independent component analysis: algorithms and applications. Neural Networks, 13(5):411-430, 2000.
9. A. Hyvärinen, J. Karhunen and E. Oja. Independent Component Analysis. John Wiley & Sons, New York, 2001.
10. J.M. Lee, S.J. Qin and LB. Lee. Fault detection and diagnosis based on modified independent component analysis. AIChE Journal, 52(10):3501-3514, 2006.