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Enhanced plant fault diagnosis based on the characterization of transient stages

Author
Monroy, I.; Benitez, R.; Escudero, G.; Graells, M.
Type of activity
Journal article
Journal
Computers & chemical engineering
Date of publication
2011-12-05
Volume
37
First page
200
Last page
213
DOI
https://doi.org/10.1016/j.compchemeng.2011.12.006 Open in new window
Project funding
Aplicación de técnicas de análisis de sistemas complejos al estudio de problemas de fisiología cardíaca.
DPI2009-09386
Repository
http://hdl.handle.net/2117/14671 Open in new window
URL
http://www.sciencedirect.com/science/article/pii/S0098135411003437 Open in new window
Abstract
This paper introduces a data-based fault diagnosis system that includes an enhanced characterization of faults during transient stages. First, data under abnormal operating conditions (AOC) is projected onto a reference PCA model constructed with data under normal operating conditions (NOC). T2 and Q-statistic measures of this first PCA model are both used to detect the fault and to estimate the duration and delay of its transient evolution. After a dimensionality reduction, a second NOC PCA mod...
Citation
Monroy, I. [et al.]. Enhanced plant fault diagnosis based on the characterization of transient stages. "Computers & chemical engineering", 05 Desembre 2011, vol. 37, p. 200-213.
Group of research
ANCORA - Anàlisi i control del ritme cardíac
CEPIMA - Centre d'Enginyeria de Processos i Medi Ambient
CREB - Biomedical Engineering Research Centre
GPLN - Natural Language Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
TALP - Centre for Language and Speech Technologies and Applications

Participants