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Sensor-data-driven prognosis approach of liquefied natural gas satellite plant

Repositorio: UPCommons. Portal del coneixement obert de la UPC
Escobet Canal, Antoni, Escobet Canal, Teresa, Quevedo Casín, Joseba Jokin, Molina, Adoración

This paper proposes a sensor-data-driven prognosis approach for the predictive maintenance of a liquefied natural gas (LNG) satellite plant. By using data analytics of sensors installed in the satellite plants, it is possible to predict the remaining time to refill the tank of the remote plants. In the proposed approach, the first task of data validation and correction is presented in order to transform raw data into reliable validated data. Then, the second task presents two methods for the…, This work was funded by the Spanish Ministry of Economy and Competitiveness (MINECO) and FEDER through projects SCAV (ref. DPI2017-88403-R), and by AGAUR ACCIO RIS3CAT UTILITIES 4.0–P1 ACTIV 4.0. ref. COMRDI-16-1-0054-03 and SMART Project (ref no EFA153/16 Interreg Cooperation Program POCTEFA 2014- 2020)., Peer Reviewed