General objective: This project´s general objective is to investigate and design new techniques based on Edge Computing and Deep Learning for the predictive maintenance of wind turbine farms and the optimisation of the planning of maintenance interventions at preventive, corrective and predictive level. As the main result of this research project, a Deep Learning and Edge Computing platform will be built for the predictive maintenance of renewable facilities by means of Deep NeuroFuzzy algorithms, as well as multi-criteria optimisation algorithms for the recommendation of the ideal moments to carry out the different maintenance interventions on wind turbines.
File number: RTC2019-006912-3
Project budget: 892,834.80 €.
ETULOS SOLUTE budget: 293,861.60 €.
Collaborating partners: USAL and PROYECTA RENOVABLES CONTROL
Funding body: State Research Agency