DocumentCode
3525139
Title
A new method for determining PCA models for system diagnosis
Author
Benaicha, Anissa ; Mourot, Gilles ; Guerfel, Mohamed ; Benothman, Kamel ; Ragot, José
Author_Institution
Res. Unit ATSI, Nat. Eng. Sch. of Monastir, Monastir, Tunisia
fYear
2010
fDate
23-25 June 2010
Firstpage
862
Lastpage
867
Abstract
In this paper, a new method is proposed to determine the structure of PCA models for system diagnosis. This method based on the principle of variable reconstruction determines PCA models in order to optimize detection and isolation of simple and multiple faults affecting redundant or non redundant variables. This new method has been validated by a simulation example of a nonlinear system.
Keywords
fault diagnosis; optimisation; principal component analysis; PCA models structure; fault detection optimisation; nonlinear system; nonredundant variables; system diagnosis; variable reconstruction principle; Covariance matrix; Data models; Eigenvalues and eigenfunctions; Fault detection; Indexes; Principal component analysis; Signal to noise ratio; PCA; fault detection and isolation; number of principal components; sensor fault; variable reconstruction;
fLanguage
English
Publisher
ieee
Conference_Titel
Control & Automation (MED), 2010 18th Mediterranean Conference on
Conference_Location
Marrakech
Print_ISBN
978-1-4244-8091-3
Type
conf
DOI
10.1109/MED.2010.5547762
Filename
5547762
Link To Document