DocumentCode
3469067
Title
Monitoring approach using Nonlinear Principal Component Analysis
Author
Ouni, K. ; Dhouibi, H. ; Nabli, L. ; Messaoud, Hassani ; Simeu-Abazi, Zineb
Author_Institution
UR ATSI D.Genie Electr. de L´ENIM, Monastir, Tunisia
fYear
2011
fDate
3-5 March 2011
Firstpage
1
Lastpage
6
Abstract
This paper presents fault detection and diagnosis based on Neural Non Linear Principal Component Analysis (NNLPCA) and a Partial Least Square (PLS). A new process monitoring method is proposed and is applied to fault detection of a manufacturing process. The performance of the proposed approach is then illustrated and compared to those of classic LPCA.
Keywords
fault diagnosis; manufacturing processes; monitoring; principal component analysis; fault detection; fault diagnosis; manufacturing process; monitoring; neural nonlinear principal component analysis; partial least square; Artificial neural networks; Biological neural networks; Fault detection; Mathematical model; Neurons; Principal component analysis; Training; Fault diagnosis; Neural Nonlinear Principal Component Analysis; Partial Least Square; cluster;
fLanguage
English
Publisher
ieee
Conference_Titel
Communications, Computing and Control Applications (CCCA), 2011 International Conference on
Conference_Location
Hammamet
Print_ISBN
978-1-4244-9795-9
Type
conf
DOI
10.1109/CCCA.2011.6031486
Filename
6031486
Link To Document