JEC Composites Innovation Awards Ceremony 2024 - Digital, AI & Data

Discover the Digital, AI & Data category with the 3 finalists and the winner of the JEC Composites Innovation Awards!

Digital, AI & Data category
AI Solutions Improve Sustainability & Reduce Waste
Plataine (Israel)

Mobile Energy Analysis for Sustainable Production
CTC GmbH (Germany)

Wind Turbine Blade Executable Digital Twin
ReliaBlade (Denmark)

ReliaBlade (Denmark)
• CEKO Sensors (Denmark)
• FORCE Technology (Denmark)
• Siemens Industry Software (SISW) (Belgium)
• Technical University of Denmark (Denmark)
• Zebicon (Denmark)

The wind turbine blade executable Digital Twin combines a reduced-order model with live sensor signal to assess structural performance in real-time. Physical and virtual sensors combined is key to perform Structural Health Monitoring.

The 12.6m wind turbine blade is manufactured using a conventional vacuum infusion process at DTU BladeLab. Non-crimp UD and BIAX fiberglass fabrics, sandwich core material and root inserts are placed as dry layup in the molds. Subsequently, vacuum infusion processes are conducted for each of the parts using an epoxy resin system. After the shells and webs have been infused and fully cured, the two airfoil shells and shear webs are bonded together using epoxy adhesive before the blade is trimmed.

Key benefits:
• Live monitoring of blade deformations
• Live monitoring of loads and remaining life
• Predictive maintenance assessment
• Remote monitoring and health assessment
• Model error reduction

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