Title :
PLS-based FDI of a Three-Tank laboratory system
Author :
Klinkhieo, S. ; Patton, R.J.
Author_Institution :
Dept. of Eng., Univ. of Hull, Kingston upon Hull, UK
Abstract :
The problems of fault detection and isolation of dynamic systems has been studied intensively in the recent years and many successful industrial applications have been reported. In the main these studies have been restricted to model based techniques, with few reports of successful implementation of data driven approaches. These data driven approaches have been range from the application of linear regression techniques, to neuro-fuzzy systems. This paper reports on application of, Multivariate Statistical Process Control (MSPC) methodologies, which can provide a diagnostic tool for the on-line or real time monitoring and detection of the process malfunction is proposed. Finally the effectiveness of Partial Least Squares (PLS) in FDI of the three-tank system are represented and discussed through simulation results.
Keywords :
computerised monitoring; data handling; fault diagnosis; fuzzy neural nets; least squares approximations; linear systems; regression analysis; statistical process control; PLS-based FDI; data driven approaches; dynamic systems; fault detection; fault isolation; model based techniques; multivariate statistical process control; partial least squares; three-tank laboratory system; Electrical equipment industry; Fault detection; Fault diagnosis; Fuzzy neural networks; Laboratories; Least squares methods; Linear regression; Monitoring; Principal component analysis; Process control;
Conference_Titel :
Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3871-6
Electronic_ISBN :
0191-2216
DOI :
10.1109/CDC.2009.5400848
