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A fault/anomaly system prognosis using a data-driven approach considering uncertainty

Author
Escobet, T.; Quevedo, J.; Puig, V.
Type of activity
Presentation of work at congresses
Name of edition
WCCI - IEEE World Congress on Computational Intelligence
Date of publication
2012
Presentation's date
2012-06-12
Book of congress proceedings
IEEE World Congress on Computational Intelligence
First page
2325
Last page
2331
DOI
https://doi.org/10.1109/IJCNN.2012.6252688 Open in new window
Repository
http://hdl.handle.net/2117/17073 Open in new window
Abstract
This paper presents a data-driven prognostic strategy for failure prediction and computing the remaining useful life (RUL) using an autoregressive (AR) model combined with the recursive least squares (RLS) algorithm. The proposed method not only provides an estimation of the remaining useful life (RUL), but also a confidence interval based on modeling the uncertainty as a probabilistic Gaussian variable. To illustrate the performance of the proposed approach, a conveyor belt system that uses an ...
Citation
Escobet, T.; Quevedo, J.; Puig, V. A fault/anomaly system prognosis using a data-driven approach considering uncertainty. A: IEEE World Congress on Computational Intelligence. "IEEE World Congress on Computational Intelligence". Brisbane: 2012, p. 2325-2331.
Group of research
CS2AC-UPC - Supervision, Safety and Automatic Control
SAC - Advanced Control Systems

Participants