Project description DEENESFRITPL 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. Show the project objective Hide the project objective 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 natural sciencescomputer and information sciencesartificial intelligenceengineering and technologyenvironmental engineeringenergy and fuelsrenewable energywind powerengineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors Programme(s) H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs Main Programme H2020-EU.3. - PRIORITY 'Societal challenges H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies Topic(s) EIC-SMEInst-2018-2020 - SME instrument Call for proposal H2020-EIC-SMEInst-2018-2020 See other projects for this call Sub call H2020-SMEInst-2018-2020-1 Funding Scheme SME-1 - SME instrument phase 1 Coordinator VERTIKAL AI APS Net EU contribution € 50 000,00 Address JYLLANDSGADE 8, 1 7100 VEJLE Denmark See on map SME The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed. Yes Region Danmark Syddanmark Sydjylland Activity type Private for-profit entities (excluding Higher or Secondary Education Establishments) Links Contact the organisation Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 71 429,00
