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Combining learning in model space fault diagnosis with data validation/reconstruction: Application to the Barcelona water network

Autor
Quevedo, J.; Chen, H.; Cuguero-Escofet, M.A.; Tino, P.; Puig, V.; García, D.; Sarrate, R.; Yao, X.
Tipus d'activitat
Article en revista
Revista
Engineering applications of artificial intelligence
Data de publicació
2014-02-14
Volum
30
Pàgina inicial
18
Pàgina final
29
DOI
https://doi.org/10.1016/j.engappai.2014.01.008 Obrir en finestra nova
Projecte finançador
MAKING SENSE OF NONSENSE
Repositori
http://hdl.handle.net/2117/23031 Obrir en finestra nova
Resum
In this paper, an integrated data validation/reconstruction and fault diagnosis approach is proposed for critical infrastructure systems. The proposed methodology is implemented in a two-stage approach. In the first stage, sensor communication faults are detected and corrected, in order to facilitate a reliable dataset to perform system fault diagnosis in the second stage. On the one hand, sensor validation and reconstruction are based on the combined use of spatial and time series models. Spati...
Citació
Quevedo, J. [et al.]. Combining learning in model space fault diagnosis with data validation/reconstruction: Application to the Barcelona water network. "Engineering applications of artificial intelligence", 14 Febrer 2014, vol. 30, p. 18-29.
Paraules clau
Fault diagnosis, Learning in model space, Reservoir computing, Sensor data validation/reconstruction, Time series
Grup de recerca
CS2AC-UPC - Supervision, Safety and Automatic Control
SAC - Sistemes Avançats de Control
SIC - Sistemes Intel·ligents de Control

Participants