AI for Predictive Maintenance on Wind Turbines

Projektinformationen

PAVIMON

ID Finanzhilfevereinbarung: 885916

DOI

10.3030/885916

Projekt abgeschlossen

EK-Unterschriftsdatum 25 Oktober 2019

Startdatum 1 Oktober 2019

Enddatum 29 Februar 2020

Finanziert unter

• INDUSTRIAL LEADERSHIP - Innovation In SMEs

Gesamtkosten

€ 71 429,00

EU-Beitrag

€ 50 000,00

Koordiniert durch

VERTIKAL AI APS
Denmark

Periodic Reporting for period 1 - PAVIMON (AI for Predictive Maintenance on Wind Turbines)

Berichtszeitraum: 2019-10-01 bis 2020-02-29

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

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. Vertikal AI is focused on the implementation of advanced artificial intelligence (AI) to analyze data from wind turbine sensor data streams. The aim is to increase the resource efficiency of signal analysis and improve predictive capabilities. The PAVIMON project was a feasibility study at technical, transformational and commercial levels - in its essence, an advanced business and market analysis.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

Through collaboration with test clients, the PAVIMON project produced key strategic guidance based on a thorough study and analysis. Technical datasets were made available for analysis as well as data science experiments. Expert interviews were conducted to analyze user experience pains of current state-of-the, gather market intelligence, and understand future technology trends. The key results were; 1) A revised product modularization strategy, 2) Validation of targeted beachhead clients, 3) Improved approach to IPR, 4) New growth strategy options identified, 5) Key risks and growth barriers based on e.g. competitive analysis.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

While executing the SME phase 1 project, Vertikal AI has matured its core product components through datasets and insights provided by test clients. Furthermore, a 2-year collaboration agreement was signed with a large European asset owner, which is an enabler for increasing speed to market.
Bringing our AI technology to market contributes significantly to lowering the cost of wind turbine operations and maintenance and thereby accelerates the transition to renewable energy. The goals of Vertikal AI align perfectly with the European Green deal. Fulfilling the potential of our technology strengthens the EU’s and Denmark’s position within artificial intelligence.

The founders of Vertikal AI: Allan Moeller Larsen (left) and Martin Bach-Andersen (right)