TY - GEN
T1 - Generalized Hebbian Algorithm for fault detection of CSTR model
AU - Baklouti, Raoudha
AU - Mansouri, Majdi
AU - Nounou, Mohamed
AU - Ben Messaoud, Zaineb
AU - Ben Hamida, Ahmed
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/26
Y1 - 2016/7/26
N2 - By applying Generalized Hebbian Algorithm (GHA), this work deals with the problem of on-line process monitoring for a continuously stirred tank reactor (CSTR) model using Principal Component Analysis (PCA) method. Diverse studies have shown the efficiency of PCA for fault detection. However, this method for a large number of samples, becomes difficult to directly solve the eigenvalue problem especially with a large number of samples, which make it not suitable in the cases of on-line process monitoring. In this paper, Iterated PCA have been proposed to alleviate the impact of this problem. This method uses GHA for optimizing the memory efficiency. The simulation results show the effectiveness of the IPCA method in terms of fault detection accuracies, false alarm rates for detection of single as well as multiple sensor faults through its two charts Q and Hotelling T2 statistics.
AB - By applying Generalized Hebbian Algorithm (GHA), this work deals with the problem of on-line process monitoring for a continuously stirred tank reactor (CSTR) model using Principal Component Analysis (PCA) method. Diverse studies have shown the efficiency of PCA for fault detection. However, this method for a large number of samples, becomes difficult to directly solve the eigenvalue problem especially with a large number of samples, which make it not suitable in the cases of on-line process monitoring. In this paper, Iterated PCA have been proposed to alleviate the impact of this problem. This method uses GHA for optimizing the memory efficiency. The simulation results show the effectiveness of the IPCA method in terms of fault detection accuracies, false alarm rates for detection of single as well as multiple sensor faults through its two charts Q and Hotelling T2 statistics.
KW - Continuously Stirred Tank Reactor
KW - Fault Detection
KW - Generalized Hebbian Algorithm
KW - iterated Principal Component Analysis
UR - http://www.scopus.com/inward/record.url?scp=84984623516&partnerID=8YFLogxK
U2 - 10.1109/ATSIP.2016.7523127
DO - 10.1109/ATSIP.2016.7523127
M3 - Conference contribution
AN - SCOPUS:84984623516
T3 - 2nd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2016
SP - 421
EP - 425
BT - 2nd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2016
Y2 - 21 March 2016 through 24 March 2016
ER -