INVESTIGADORES
BANDONI Jose Alberto
artículos
Título:
CACE-1996: ROBUST STATISTICAL PROCESS MONITORING
Autor/es:
J. CHEN; A. BANDONI; J. ROMAGNOLI
Revista:
COMPUTERS AND CHEMICAL ENGINEERING
Editorial:
PERGAMON-ELSEVIER SCIENCE LTD
Referencias:
Lugar: Amsterdam; Año: 1996 vol. 20 p. 497 - 502
ISSN:
0098-1354
Resumen:
Principal component analysis (PCA) is a key step to carrying out multivariate statistical process
monitoring. Due to the sensitive nature of classical PCA. one or two outliers will cause misleading results.
In this paper, a robust PCA via a Hybrid Proiection Pursuit (HPP) approach is proposed. Incorporation of
this robust PCA into our previously developed data driven strategy, for statistical process monitoring, will
mean the whole procedure will be resistant to outliers and thus robust. The performance of the proposed
approach is demonstrated by simulation studies on a simple flowsheet example