On the application of recursive principal component analysis method to fault detection and isolation

Autor:	Okba Taouali, H. Massaoud, Ines Jaffel, Ilyes Elaissi
Rok vydání:	2015
Předmět:	Control theory Covariance matrix Principal component analysis Perturbation (astronomy) First order perturbation Algorithm Fault detection and isolation Eigenvalues and eigenvectors Data modeling Mathematics
Zdroj:	2015 4th International Conference on Systems and Control (ICSC).
DOI:	10.1109/icosc.2015.7153296
Popis:	This communication suggests an extension of an online fault detection method [1] to fault isolation. This proposed method is titled Recursive Principal Component Analysis based on First Order Perturbation RPCA-FOP and it is based on first order perturbation theory (FOP) and partial PCA models where the eigenvalues and eigenvectors of the covariance matrix are updated taking into account the effect of new acquired data as a perturbation.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::32307dd199938ec7d5d981c932d5925c https://doi.org/10.1109/icosc.2015.7153296 Zobrazit plný text záznamu