DocumentCode :
3421262
Title :
Incipient fault detection and isolation in a PWR plant using principal component analysis
Author :
Kaistha, N. ; Upadhyaya, B.R.
Author_Institution :
University of Tennessee
Volume :
3
fYear :
2001
fDate :
25-27 June 2001
Firstpage :
2119
Lastpage :
2120
Abstract :
A method for the detection and isolation of incipient faults in field devices in industry using Principal Component Analysis (PCA) is presented. Nominal operation data typically lie on a low-dimension surface due to relationships imposed by the physics of the process and are modeled using PCA. Abnormal deviations from the surface lead to fault detection while isolation is a consequence of these deviations being in different directions for different faults. A steam generator in a pressurized water reactor (PWR) is used for demonstration.
Keywords :
Data analysis; Databases; Fault detection; Feedback control; Matrix decomposition; Monitoring; Personal communication networks; Physics; Principal component analysis; Sensor systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2001. Proceedings of the 2001
Conference_Location :
Arlington, VA, USA
ISSN :
0743-1619
Print_ISBN :
0-7803-6495-3
Type :
conf
DOI :
10.1109/ACC.2001.946059
Filename :
946059
Link To Document :
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