Project description
AI for Predictive Maintenance on Wind Turbines
Wind power is a key component in the transition towards a society based on renewable energy. However, wind turbine operation and maintenance costs remain high and represent a third of the total costs of energy. Maintenance of critical components can be drastically reduced through early fault detection using advanced sensor signals. However, current analysis methods are highly manual and do not scale well. The EU-funded PAVIMON project is focused on the implementation of advanced artificial intelligence (AI) to analyze data from these sensor streams. The aim is to increase the resource efficiency of signal analysis and improve predictive capabilities. The PAVIMON project will effectuate a feasibility study at technical, transformational and commercial levels.
Objective
Wind power is a key component in the transition towards a society based on renewable energy. However, wind turbine operation and maintenance costs remain high and represent a third of the total costs of energy. Maintenance of critical components can be drastically reduced through early fault detection using advanced sensor signals. However, current analysis methods are highly manual and do not scale well.
The EU-funded PAVIMON project is focused on the implementation of advanced artificial intelligence (AI) to analyze data from these sensor streams. The aim is to increase the resource efficiency of signal analysis and improve predictive capabilities. The PAVIMON project will effectuate a feasibility study at technical, transformational and commercial levels.
Fields of science
Not validated
Not validated
Programme(s)
Funding Scheme
SME-1 - SME instrument phase 1Coordinator
7100 VEJLE
Denmark
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.